# Proceedings of the World Congress on Engineering and Computer Science 2009 Vol II WCECS 2009, October 20-22, 2009, San Francisco, USA

Save this PDF as:

Size: px
Start display at page:

Download "Proceedings of the World Congress on Engineering and Computer Science 2009 Vol II WCECS 2009, October 20-22, 2009, San Francisco, USA"

## Transcription

2 II. THE SUPPLY CHAIN SYSTEM To find an Economic Order Quantity (EOQ) for the raw materials and an Economic Manufacturing Quantity (EMQ) for the production run, two types of inventory holding costs are considered [17]: raw materials holding cost, H, and manufactured products holding cost, H. Order costs includes the ordering cost of the raw materials, K and the manufacturing setup cost for each batch, K. Opportunity cost, OC and extra sales cost, EC considered for illustrating upper and lower demand situations costs. α, β, γ considered as demand probabilities for three different states of the customer s demand. Following notation is used to model the system: A. Definitions and Notation Raw material related:,,,, and. Manufactured products related:,,, f,,,, P,,,,,,,,, ), α, β, γ, ). Cycle time related:,,, and. Definitions: = total demand for manufactured products by all customers, units/year;, = total demand for manufactured products by customer, units/year; = total demand for raw materials by the production facility, units/year; = conversion factor of the raw materials to manufactured products, = / ; = holding cost of manufactured products, \$/unit/year; = holding cost of raw materials, \$/unit/year; = ordering cost of raw materials, \$/order; = manufacturing setup cost per batch, \$/batch; = given time between successive shipments of manufactured products to customer ( 1,, N; = number of full shipments of manufactured products to customer per cycle time ; = number of orders of raw materials during the uptime ; = production rate, units/year; = average inventory of manufactured products per cycle, in units; = quantity of manufactured products manufactured per setup, units/batch; = quantity of manufactured products inventory held at the end of uptime, in units; = manufactured products inventory on hand at time ; = quantity of manufactured products in the inventory at time, in units; = quantity of raw materials ordered each time, units/order; / ; = quantity of raw materials required for each batch; ; = total quantity of manufactured products shipped, in units/cycle; = total quantity of manufactured products shipped by time ; = cycle time; = production start time;, While = manufacturing period (uptime); ; = downtime; ; {1,...,N}; = quantity of manufactured products shipped to customer at a fixed interval of time, units/shipment;, While 1,, N; = quantity produced during period; = = ( 1 ; = opportunity cost for sale manufactured products when demand for manufactured products ( ) is more than it s calculated average ( ), \$/unit; = extra sale costs for sale manufactured products when demand for manufactured products is less than it s calculated average ( ), \$/unit; = average total demand for manufactured products by all customers, units/year; = customer s total demand probabilistic function; α = total customer s demand probability when manufactured products demand is equal to average total demand for manufactured products, (, 0 α 1; β = total customer s demand probability when manufactured products demand is less than average total demand for manufactured products, (, 0 β 1; γ = total customer s demand probability when manufactured products demand is more than average total demand for manufactured products, (, 0 γ 1; α + β + γ = 1. B. The Supply Chain System Manufactured products inventory in this model, doesn't have equal behavior comparison with traditional economic batch quantity model with continuous demand [13]. As depicted in Fig. 1, to discourage the undesirable inventory buildup, raw materials in this model are ordered times during the uptime. Because production rate,, is considered to be higher than the consumption rate, the inventory will keep on building while the production (or uptime) continues. A fluctuating-demand (fixed quantity) of units of manufactured products at the end of every time units to customer,( 1,2,, N, is imposed to the manufacturer. This fluctuating demand decreases the

3 manufactured products inventory buildup instantaneously by that makes as a result, an inventory buildup in an increasing triangular fashion during the production period. units of manufactured products, to satisfy the demand of customer at an interval of time units, are delivered instantaneously that as a result remains units at hand, where, the quantity that produced during time units at the rate of units per unit-time. The delivery schedules of manufactured products and quantities shipped to customer,( 1,2,, N, are also shown in Fig. 1. For customers and all,( 1,2,, N, may not be equal and,( 1,2,, N, the number of full shipments to customer, is a non increasing set of integer numbers ( such that =. The on-hand manufactured products inventory at any time is the manufactured products produced by that time minus the total inventory delivered to all customers by time. the on-hand manufactured products at the end of uptime period,, decrease instantaneously by units at a regular interval of time units (after the production run) till the end of the last shipment in a cycle are carried over to the next cycle, resulting in a shifted production schedule as reflected in Fig. 1.[17] Fig.1. Raw materials and manufactured products inventory [17] III. PRODUCTION COST MODEL We assume that. and to be more confident in case of materials availability and proper delivery, we further assume that and, While {1,2,,N}. A. Total Cost Functions In the our model we assume that total future demand for manufactured products is equal to demand probability function expected value. System has costs as below: A.1. Raw Material Costs In an inventory state where = = =, there might be some manufactured products hands over to the next cycle after shipments to all customers. A series of fluctuating deliveries of manufactured products inventory continues after until the cycle repeats same as what that done before. Thus the total cost of raw materials, as stated with Sarker and Parija[13], is given by. (1) Now, if there are replenishments of raw materials during the uptime period [,, and transports of manufactured products of size to customer,( 1,2,, N, during the cycle time, then, for, each batch required raw materials, we can write / and = = =. therefore equation (1) could rewrite as below:. (2) A.2 Manufactured Products Costs Because of probabilistic changes that exist in the demand of manufactured products, three different demand states maybe arise during the planning time horizon. A.2.1 When manufactured products demand ( is equal to expected value for manufactured products demand (, we have this state for system costs (when ). Since = and = for a conversion factor (or production process efficiency) of raw materials to manufactured products,, the total cost for manufactured products inventory for average inventory at a holding cost \$/unit/year can also be written as[17]. (3) and the entire cost of the system may be expressed as,. (4) Therefore, with replacing in equation (4) with the results from what that stated by Sarker and Parija [17]:,. (5) A.2.2 In this state manufactured products costs could formulate as below: ). (6) Therefore, replacing in equation (6) with the results from Sarker s study[17] and with regarding raw material costs from equation (2) in section we have, ). (7) A.2.3 In this state manufactured products costs could formulate as below: ). (8) Therefore, replacing in equation (8) with the results from Sarker s results[17] and with regarding raw material costs from equation (2) in section we have

4 ,. (9) As mentioned, three different total cost functions as three different scenarios exists for different states of the entire system base on its total manufactured products demands. Now, if is a time such that, then must satisfy[17] / While. (10) That is, the quantity of manufactured products produced in the time interval, is sufficient to meet the demands (shipments) for each individual customer until the time, at all times, after the product begins at. Theorem 1. [17] If Min Subject to, / / 1 for 1,2,,, and : real, : integer, then satisfies the inequality (10). (11) The lower bound on the integer variable will be very useful in actual computations. In theorem 1, illustrated that if is chosen as stated, then meeting demands for all the products will guarantee. B. Start Time Determination[17] The production start time,, can be determined by solving the problem: (PST):, Subject to /, While 0. (12) This means that we would like to delay starting the procurement and the production until it is absolutely necessary. The constraint in problem (PST) implies that, if i) The quantity of manufactured products produced in the interval, is ; ii) is the number of shipments for customer ; iii) is the total shipment quantity to customer time, until time, until Then the quantity produced in the interval, is enough to meet the demands for all the customers until time. Note that the constraint in (PST) can be written as :, 0, = 0, equivalent to the inequality (13) which is Min 1, 0, 0 and integer. (14) The right-hand side of inequality (13) is a Mixed-Integer Programming (MIP) problem. Therefore, the upper bound on is the solution of the MIP in inequality (13). Hence, the optimal production start time T is given clearly by [17] T Min 1, 0, 0 and integer. (15) IV. SOLUTION ALGORITHM Algorithm 1 as a strategy to arrive at a feasible solution for this problem could be use. Algorithm 1: solution algorithm 1. Compute by solving the MIP in (15) 2. Compute,,, and,. 3. Obtain probabilistic weighted total cost function, :,,,, /, +, +, ) (15) 4. Minimize, over to obtain (, ) 5. Obtain a pragmatic solution: (a) Generate two feasible integer solutions in the neighborhood of (, ). max constant for all, 1, :integer, max constant for all, 1, :integer, = Integer n such that n minimizes ( / / ), and = Integer n such that n minimizes ( / / ). b Choose the better of the two candidate solutions: Optimum, = / ) where k = arg min {PWTC ( / ), i = {0,1}} V. CONCLUSION The situation that developed in this paper was about demand behavior. In the previous research demand considered as a fix parameter that we manufacturer efforts to balance its raw materials and manufactured products inventory to achieve minimum total cost for the entire system but in this paper we focused on the behavior of demand and assumed that demand has a probabilistic scenario based behavior and for each alternative we have an specified total cost function that the goal of the model is to minimize the probabilistic weighted total cost function for the entire system Future researches can be directed to considering more probabilistic sub-systems and factors in the different combinations of inventory-production-sale or value chain systems. REFERENCES [1] Newman, R.G. (1988) the buyer-supplier relationship under just in time. Production and Inventory Management, 29(3), [2] Yilmaz, C. (1992) Incremental order quantity for the case of very lumpy demand. International Journal of Production Economics, 26(3), [3] Parlar, M. and Rempala, R. (1992) A stochastic inventory problem with piecewise quadratic costs. International Journal of Production Economics, 26(3), [4] Pan, A.C. and Liao, C.J. (1989) An inventory model under just-in-time purchasing agreements. Production and Inventory Management, 30(1),

5 [5] Ramasesh, R.V. (1990) Recasting the traditional inventory model to implement just-in-time purchasing. Production and Inventory Management, 31(1), [6] Lu, L. (1995) A one-vendor multi-buyer integrated inventory model. European Journal of Operational Research, 81(3), [7] Goyal, S.K. (1995) A one-vendor multi-buyer integrated inventory model: a comment. European Journal of Operational Research, 82(2), [8] Goyal, S.K. and Gupa, Y.P. (1989) Integrated inventory models: the buyer-vendor coordination. European Journal of Operational Research, 41(2), [9] Aderohunmu, R., Mobolurin, A. and Bryson, N. (1995) Joint vendor-buyer policy in JIT manufacturing. Journal of the Operational Research Society, 46(3), [10] Golhar, D.Y. and Sarker, B.R. (1992) Economic manufacturing quantity in a just-in-time delivery system. International Journal of Production Research, 30(5), [11] Jamal, A.M.M. and Sarker, B.R. (1993) An optimal batch size for a production system operating under a just-in-time delivery system. International Journal of Production Economics, 32(2), [12] Sarker, B.R. and Parija, G.R. (1994) An optimal batch size for a production system operating uner fixed-quantity, periodic delivery policy. Journal of Operational Research Society, 45(8), [13] Sarker, B.R. and Parija, G.R. (1996) Optimal batch size and raw material ordering policy for a production system with a fixed-interval, lumpy demand delivery system. European Journal of Operational Research, 89(3), [14] Banerjee, A. (1992) Production lot sizing with work-in-process considerations in response to periodic demand. International Journal of Production Economics, 26(2), [15] Park, K.S. and Yun, D.K. (1984) A stepwise partial enumeration algorithm for the economic lot scheduling problem. IIE Transactions, 16(4), [16] Nori, V.S. and Sarker, B.R. (1996) Cyclic scheduling for a multi-product, single-facility production system operating under a just-in-time policy. Journal of Operational Research Society, 47(7), [17] Sarker, B.R. and Parija, G.R. (1999) Operations planning in a supply chain system with fixed-interval deliveries of finished goods to multiple customers. IIE Transactions, 31(1), [18] Robert N. Boute, Stephen M. Disney, Marc R. Lambrecht, Benny Van Houdt. (2007) An integrated production and inventory model to dampen upstream demand variability in the supply chain. European Journal of Operational Research, 178, [19] Liang-Yuh Ouyanga, Kun-Shan Wub, Chia-Huei Ho. (2004) Integrated vendor buyer cooperative models with stochastic demand in controllable lead time. Int. J. Production Economics, 92, [20] ManMohan S.Sodhi, ChristopherS.Tang. (2007) Modeling supply-chain planning under demand uncertainty using stochastic programming: A survey motivated by asset liability management. Int. J. Production Economics, ARTICLE IN PRESS. [21] ] M.E. Seliaman, Ab Rahman Ahmad. (2008) Optimizing inventory decisions in a multi-stage supply chain under stochastic demands. Applied Mathematics and Computation, 206,

### An integrated Single Vendor-Single Buyer Production Inventory System Incorporating Warehouse Sizing Decisions 창고 크기의사결정을 포함한 단일 공급자구매자 생산재고 통합관리 시스템

Journal of the Korean Institute of Industrial Engineers Vol. 40, No. 1, pp. 108-117, February 2014. ISSN 1225-0988 EISSN 2234-6457 http://dx.doi.org/10.7232/jkiie.2014.40.1.108 2014 KIIE

### An Integrated Production Inventory System for. Perishable Items with Fixed and Linear Backorders

Int. Journal of Math. Analysis, Vol. 8, 2014, no. 32, 1549-1559 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ijma.2014.46176 An Integrated Production Inventory System for Perishable Items with

### International Journal of Advances in Science and Technology (IJAST)

Determination of Economic Production Quantity with Regard to Machine Failure Mohammadali Pirayesh 1, Mahsa Yavari 2 1,2 Department of Industrial Engineering, Faculty of Engineering, Ferdowsi University

### An integrated just-in-time inventory system with stock-dependent demand

An integrated just-in-time inventory system with stock-dependent demand 1 Mohd Omar, 2 Hafizah Zulkipli 1,2 Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur, Malaysia 1 mohd@um.edu.my,

### FUZZY APPROACH ON OPTIMAL ORDERING STRATEGY IN INVENTORY AND PRICING MODEL WITH DETERIORATING ITEMS

International Journal of Pure and Applied Mathematics Volume 87 No. 03, 65-80 ISSN: 3-8080 (printed version; ISSN: 34-3395 (on-line version url: http://www.ijpam.eu doi: http://dx.doi.org/0.73/ijpam.v87i.0

### OPTIMAL POLICY FOR A SIMPLE SUPPLY CHAIN SYSTEM WITH DEFECTIVE ITEMS AND RETURNED COST UNDER SCREENING ERRORS

Journal of the Operations Research Society of Japan 2009, Vol. 52, No. 3, 307-320 OTIMAL OLICY FOR A SIMLE SULY CHAIN SYSTEM WITH DEFECTIVE ITEMS AND RETURNED COST UNDER SCREENING ERRORS Tien-Yu Lin Overseas

### Inventory Management - A Teaching Note

Inventory Management - A Teaching Note Sundaravalli Narayanaswami W.P. No.2014-09-01 September 2014 INDIAN INSTITUTE OF MANAGEMENT AHMEDABAD-380 015 INDIA Inventory Management - A Teaching Note Sundaravalli

### INTEGRATED OPTIMIZATION OF SAFETY STOCK

INTEGRATED OPTIMIZATION OF SAFETY STOCK AND TRANSPORTATION CAPACITY Horst Tempelmeier Department of Production Management University of Cologne Albertus-Magnus-Platz D-50932 Koeln, Germany http://www.spw.uni-koeln.de/

### D Lab: Supply Chains

D Lab: Supply Chains Inventory Management Class outline: Roles of inventory Inventory related costs Types of inventory models Focus on EOQ model today (Newsvender model next class) Stephen C. Graves 2013

### THE IMPLEMENTATION OF VENDOR MANAGED INVENTORY IN THE SUPPLY CHAIN WITH SIMPLE PROBABILISTIC INVENTORY MODEL

THE IMPLEMENTATION OF VENDOR MANAGED INVENTORY IN THE SUPPLY CHAIN WITH SIMPLE PROBABILISTIC INVENTORY MODEL Ika Deefi Anna Departement of Industrial Engineering, Faculty of Engineering, University of

### Integer Programming Model for Inventory Optimization for a Multi Echelon System

Journal of Advanced Management Science Vol, No, January 06 Integer Programming Model for Inventory Optimization for a Multi Echelon System Bassem H Roushdy Basic and Applied Science, Arab Academy for Science

### MAINTAINING A SEAMLESS SUPPLY CHAIN OF ESSENTIAL MEDICINES [A COMBINATION OF VARIOUS CONCEPTS CONVERGING INTO A NOVEL P 3 SYSTEM]

MAINTAINING A SEAMLESS SUPPLY CHAIN OF ESSENTIAL MEDICINES [A COMBINATION OF VARIOUS CONCEPTS CONVERGING INTO A NOVEL P 3 SYSTEM] Dr Pradeep J. Jha 1 LJ College of Engineering & Technology, Ahmedabad INDIA

### Spreadsheet Heuristic for Stochastic Demand Environments to Solve the Joint Replenishment Problem

, July 3-5, 2013, London, U.K. Spreadsheet Heuristic for Stochastic Demand Environments to Solve the Joint Replenishment Problem Buket Türkay, S. Emre Alptekin Abstract In this paper, a new adaptation

### Modeling Stochastic Inventory Policy with Simulation

Modeling Stochastic Inventory Policy with Simulation 1 Modeling Stochastic Inventory Policy with Simulation János BENKŐ Department of Material Handling and Logistics, Institute of Engineering Management

### INDUSTRIAL STATISTICS AND OPERATIONAL MANAGEMENT. 7. Inventory Management

INDUSTRIAL STATISTICS AND OPERATIONAL MANAGEMENT 7. Inventory Management Dr. Ravi Mahendra Gor Associate Dean ICFAI Business School ICFAI HOuse, Nr. GNFC INFO Tower S. G. Road Bodakdev Ahmedabad-380054

### APICS Dictionary Inventory Terms

Inputs Transformation Process Throughput Managing Operations: A Focus on Excellence Cox, Blackstone, and Schleier, 2003 Chapter 15 The Tools of Finished Goods Inventory Management: Traditional Methods

### Economic Production Quantity (EPQ) Model with Time- Dependent Demand and Reduction Delivery Policy

ISSN NO:: 348 537X Economic Production Quantity (EPQ) Model with Time- Dependent Demand and Reduction Delivery Policy Dr. Neeraj Agarwal Professor & Head, Department of Hotel Management, Graphic Era University,

### Optimal Policy for Vendor-Buyer Integrated Inventory Model within Just In Time in Fuzzy Environment

Intern. J. Fuzzy Mathematical Archive Vol., 013, 6-35 ISSN: 30 34 (P), 30 350 (online) Published on August 013 www.researchmathsci.org International Journal of Optimal Policy for Vendor-Buyer Integrated

### Multiproduct Batch Production and Truck Shipment Scheduling under Different Shipping Policies

Multiproduct Batch Production and Truck Shipment Scheduling under Different Shipping Policies Ümit Sağlam 1+, Avijit Banerjee 1, Chang-Hyun Kim 1 1 Department of Decision Sciences, LeBow College of Business,

### Implementation of Inventory Management System in a Furniture Company: A Real Case study

International Journal of Engineering and Technology Volume 2 No. 8, August, 2012 Implementation of Inventory Management System in a Furniture Company: A Real Case study 1 Syed Adeel Haneed Zaidi, 2 Sharfuddin

### Keywords: Single-vendor Inventory Control System, Potential Demand, Machine Failure, Participation in the Chain, Heuristic Algorithm

Indian Journal of Fundamental and Applied Life Sciences ISSN: 31 63 (Online) An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/01/03/jls.htm 01 Vol. (S3), pp. 1781-1790/Valiporian

### EXPONENTIAL DEPENDENT DEMAND RATE ECONOMIC PRODUCTION QUANTITY (EPQ) MODEL WITH FOR REDUCTION DELIVERY POLICY

SRJHSEL/BIMONHLY/ NEERAJ AGARWAL (248-2415) EXPONENIAL DEPENDEN DEMAND RAE ECONOMIC PRODUCION QUANIY (EPQ) MODEL WIH FOR REDUCION DELIVERY POLICY Neeraj Agarwal Department of Hotel Management, Graphic

### A One-Vendor Multiple-Buyer Production-Distribution System: Vendor-Managed Inventory and Retailer-Managed Inventory

A One-Vendor Multiple-Buyer Production-Distribution System: Vendor-Managed Inventory and Retailer-Managed Inventory Xiao Huang Department of Decision Sciences and MIS, Concordia University, Montreal, Quebec,

### Optimal lot size of EPQ model considering imperfect and defective products. S. R. Hejazi

Journal of Industrial Engineering International July 008, Vol. 4, No. 7, 59-68 Islamic Azad University, South Tehran Branch imal lot size of E model considering imperfect and defective products S. R. Hejazi

### Inventory Management: Fundamental Concepts & EOQ. Chris Caplice ESD.260/15.770/1.260 Logistics Systems Oct 2006

Inventory Management: Fundamental Concepts & EOQ Chris Caplice ESD.260/15.770/1.260 Logistics Systems Oct 2006 Agenda Wrap up of Demand Forecasting Fundamentals of Inventory Management Economic Order Quantity

### Analysis of a Production/Inventory System with Multiple Retailers

Analysis of a Production/Inventory System with Multiple Retailers Ann M. Noblesse 1, Robert N. Boute 1,2, Marc R. Lambrecht 1, Benny Van Houdt 3 1 Research Center for Operations Management, University

### A QUEUEING-INVENTORY SYSTEM WITH DEFECTIVE ITEMS AND POISSON DEMAND. bhaji@usc.edu

A QUEUEING-INVENTORY SYSTEM WITH DEFECTIVE ITEMS AND POISSON DEMAND Rasoul Hai 1, Babak Hai 1 Industrial Engineering Department, Sharif University of Technology, +98-1-66165708, hai@sharif.edu Industrial

### Optimizing Replenishment Intervals for Two-Echelon Distribution Systems with Fixed Order Costs

Optimizing Replenishment Intervals for Two-Echelon Distribution Systems with Fixed Order Costs Kevin H. Shang Sean X. Zhou Fuqua School of Business, Duke University, Durham, North Carolina 27708, USA Systems

### The Multi-Item Capacitated Lot-Sizing Problem With Safety Stocks In Closed-Loop Supply Chain

International Journal of Mining Metallurgy & Mechanical Engineering (IJMMME) Volume 1 Issue 5 (2013) ISSN 2320-4052; EISSN 2320-4060 The Multi-Item Capacated Lot-Sizing Problem Wh Safety Stocks In Closed-Loop

### Fuzzy Inventory Model without Shortages Using Signed Distance Method

Applied Mathematics & Information Sciences 1(2)(2007), 203-209 An International Journal c 2007 Dixie W Publishing Corporation, U. S. A. Fuzzy Inventory Model without Shortages Using Signed Distance Method

### An optimal batch size for a JIT manufacturing system

Comuters & Industrial Engineering 4 (00) 17±136 www.elsevier.com/locate/dsw n otimal batch size for a JIT manufacturing system Lutfar R. Khan a, *, Ruhul. Sarker b a School of Communications and Informatics,

### Balancing Responsiveness and Economics in Process Supply Chain Design with Multi-Echelon Stochastic Inventory

Carnegie Mellon University Research Showcase @ CMU Department of Chemical Engineering Carnegie Institute of Technology 9-2009 Balancing Responsiveness and Economics in Process Supply Chain Design with

### Teaching Manual-Operation Management. Gunadarma University. Week : 9 Subject : INVENTORY MANAGEMENT Content :

Week : 9 Subject : INVENTORY MANAGEMENT Content : WHY INVENTORY a. One of the most expensive assets of many companies representing as much as 50% of total invested capital b. Operations managers must balance

### A Profit-Maximizing Production Lot sizing Decision Model with Stochastic Demand

A Profit-Maximizing Production Lot sizing Decision Model with Stochastic Demand Kizito Paul Mubiru Department of Mechanical and Production Engineering Kyambogo University, Uganda Abstract - Demand uncertainty

### INVENTORY MODELS WITH STOCK- AND PRICE- DEPENDENT DEMAND FOR DETERIORATING ITEMS BASED ON LIMITED SHELF SPACE

Yugoslav Journal of Operations Research Volume 0 (00), Number, 55-69 0.98/YJOR00055D INVENTORY MODELS WITH STOCK- AND PRICE- DEPENDENT DEMAND FOR DETERIORATING ITEMS BASED ON LIMITED SHELF SPACE Chun-Tao

### Agenda. Real System, Transactional IT, Analytic IT. What s the Supply Chain. Levels of Decision Making. Supply Chain Optimization

Agenda Supply Chain Optimization KUBO Mikio Definition of the Supply Chain (SC) and Logistics Decision Levels of the SC Classification of Basic Models in the SC Logistics Network Design Production Planning

### Chapter 9 Managing Inventory in the Supply Chain

Chapter 9 Managing Inventory in the Supply Chain Inventory is an asset on the balance sheet and inventory cost is an expense on the income statement. Inventories impacts return on asset (ROA) Inventory

### Logistics Management Inventory Cycle Inventory. Özgür Kabak, Ph.D.

Logistics Management Inventory Cycle Inventory Özgür Kabak, Ph.D. Role of Inventory in the Supply Chain Improve Matching of Supply and Demand Improved Forecasting Reduce Material Flow Time Reduce Waiting

### FIXED CHARGE UNBALANCED TRANSPORTATION PROBLEM IN INVENTORY POOLING WITH MULTIPLE RETAILERS

FIXED CHARGE UNBALANCED TRANSPORTATION PROBLEM IN INVENTORY POOLING WITH MULTIPLE RETAILERS Ramidayu Yousuk Faculty of Engineering, Kasetsart University, Bangkok, Thailand ramidayu.y@ku.ac.th Huynh Trung

### MODELLING OF COORDINATING PRODUCTION AND INVENTORY CYCLES IN A MANUFACTURING SUPPLY CHAIN INVOLVING REVERSE LOGISTICS

MODELLING OF COORDINATING PRODUCTION AND INVENTORY CYCLES IN A MANUFACTURING SUPPLY CHAIN INVOLVING REVERSE LOGISTICS Submitted by Jonrinaldi to the University of Exeter as a thesis for the degree of Doctor

### A New System Dynamics Distribution Network Simulation Model with Uncertain Demands for Analyzing Lead Times Effect

6th International Conference on Industrial Engineering and Industrial Management. XVI Congreso de Ingeniería de Organización. Vigo, July 18-2, 212 A New System Dynamics Distribution Network Simulation

### COORDINATION IN THE SUPPLY CHAIN: VENDOR MANAGED INVENTORY IS THE WAY TO GO

www.sjm.tf.bor.ac.yu Serbian Journal of Management 1 (1) (2006) 41-47 Serbian Journal of Management COORDINATION IN THE SUPPLY CHAIN: VENDOR MANAGED INVENTORY IS THE WAY TO GO R. Piplani * Center for Supply

### An Entropic Order Quantity (EnOQ) Model. with Post Deterioration Cash Discounts

Int. J. Contemp. Math. Sciences, Vol. 6,, no. 9, 93-939 An Entropic Order Quantity (EnOQ Model with Post Deterioration Cash Discounts M. Pattnaik Dept. of Business Administration, Utkal University Bhubaneswar-754,

### A MANAGER S ROADMAP GUIDE FOR LATERAL TRANS-SHIPMENT IN SUPPLY CHAIN INVENTORY MANAGEMENT

A MANAGER S ROADMAP GUIDE FOR LATERAL TRANS-SHIPMENT IN SUPPLY CHAIN INVENTORY MANAGEMENT By implementing the proposed five decision rules for lateral trans-shipment decision support, professional inventory

### Chapter 14 Inventory Management

Chapter 14 Inventory Management Overview Nature of Inventories Opposing Views of Inventories Fixed Order Quantity Systems Fixed Order Period Systems Other Inventory Models Some Realities of Inventory Planning

### A simulation study on supply chain performance with uncertainty using contract. Creative Commons: Attribution 3.0 Hong Kong License

Title A simulation study on supply chain performance with uncertainty using contract Author(s) Chan, FTS; Chan, HK Citation IEEE International Symposium on Intelligent Control Proceedings, the 13th Mediterrean

### An Integrated Inventory Model with Retail Price-dependent Demand in Response to Announced Supply Price Increase

International Journal of Humanities and Management Sciences (IJHMS) Volume 2, Issue 1 (2014) ISSN 2320 4044 (Online) An Integrated Inventory Model with Retail Price-dependent Demand in Response to Announced

### An Economic Order Quantity Model for Defective Items under Permissible Delay in Payments and Shortage

An Economic Order Quantity Model for Defective Items under Permissible Delay in Payments and Shortage Harun SULAK 1 Assistant Professor, Department of Econometrics, Faculty of Economics and Administrative

### Key Concepts: Week 8 Lesson 1: Inventory Models for Multiple Items & Locations

Key Concepts: Week 8 Lesson 1: Inventory Models for Multiple Items & Locations Learning Objectives Understand how to use different methods to aggregate SKUs for common inventory policies Understand how

### Optimum decision-making process for an Economic Order Quantity (EOQ) model with budget and floor space constraints

American Journal of Service Science and Management 2014; 1(5): 53-57 Published online January 20, 2015 (http://www.openscienceonline.com/journal/ajssm) Optimum decision-making process for an Economic Order

### STRATEGIC CAPACITY PLANNING USING STOCK CONTROL MODEL

Session 6. Applications of Mathematical Methods to Logistics and Business Proceedings of the 9th International Conference Reliability and Statistics in Transportation and Communication (RelStat 09), 21

### General lotsizing problem in a closed-loop supply chain with uncertain returns

General lotsizing problem in a closed-loop supply chain with uncertain returns Guillaume Amand, Yasemin Arda July 3, 2013 G. Amand and Y. Arda (HEC-Ulg) General lotsizing problem in a closed-loop supply

### Developing and solving two-echelon inventory system for perishable items in a supply chain: case study (Mashhad Behrouz Company)

AriaNezhad et al. Journal of Industrial Engineering International 2013, 9:39 CASE STUDY Open Access Developing and solving two-echelon inventory system for perishable items in a supply chain: case study

### School of Economics and Management, Tongji University, Shanghai 200092, China. Correspondence should be addressed to Bing-Bing QIU, qiubb2005@163.

Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 01, Article ID 867847, 16 pages doi:10.1155/01/867847 Research Article Distribution-Free Continuous Review Inventory Model with

### ISSN: 2277-3754 ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 3, Issue 12, June 2014

ISSN: 77-3754 ISO 9001:008 Certified International Journal of Engineering and Innovative echnology (IJEI) Volume 3, Issue 1, June 014 Optimal Preservation echnology Investment, Credit Period and Ordering

### Just-in-time purchasing: an integrated inventory model involving deterministic variable lead time and quality improvement investment

int. j. prod. res., 004, vol. 4, no. 5, 853 863 Just-in-time purchasing: an integrated inventory model involving deterministic variable lead time and quality improvement investment JIN-SHAN YANGy and JASON

### Linear Programming Notes V Problem Transformations

Linear Programming Notes V Problem Transformations 1 Introduction Any linear programming problem can be rewritten in either of two standard forms. In the first form, the objective is to maximize, the material

### Modeling Multi-Echelon Multi-Supplier Repairable Inventory Systems with Backorders

J. Service Science & Management, 2010, 3, 440-448 doi:10.4236/jssm.2010.34050 Published Online December 2010 (http://www.scirp.org/journal/jssm) Modeling Multi-Echelon Multi-Supplier Repairable Inventory

### 1. (16 pts) D = 5000/yr, C = 600/unit, 1 year = 300 days, i = 0.06, A = 300 Current ordering amount Q = 200

HW 2 Solution 1. (16 pts) D = 5000/yr, C = 600/unit, 1 year = 300 days, i = 0.06, A = 300 Current ordering amount Q = 200 (a) T * = (b) Total(Holding + Setup) cost would be (c) The optimum cost would be

### Lost Sales Inventory Model in Finite Planning Horizon

Jurnal Metris, 15 (2014): 1 6 Jurnal Metris ISSN: 1411-3287 Lost Sales Inventory Model in Finite Planning Horizon G. Mangkuharjo 1,2, Y. Agustina H. 2, Hui-Ming Wee 1 a Department of Industrial and Systems

### AN OPTIMAL POLICY INVENTORY MODEL WITH LOT SIZE DEPENDANT HOLDING COST AND SHORTAGES

International Journal of Mathematics and Computer Applications Research (IJMCAR) ISSN(P): 2249-6955; ISSN(E): 2249-8060 Vol. 4, Issue 2, Apr 2014, 29-36 TJPRC Pvt. Ltd. AN OPTIMAL POLICY INVENTORY MODEL

### EPQ MODEL FOR IMPERFECT PRODUCTION PROCESSES WITH REWORK AND RANDOM PREVENTIVE MACHINE TIME FOR DETERIORATING ITEMS AND TRENDED DEMAND

Yugoslav Journal of Operations Research 25 (25), Number 3, 425-443 DOI:.2298/YJOR3689S EPQ MODEL FOR IMPERFEC PRODUCION PROCESSES WIH REWORK AND RANDOM PREVENIVE MACHINE IME FOR DEERIORAING IEMS AND RENDED

### CHAPTER 6 AGGREGATE PLANNING AND INVENTORY MANAGEMENT 명지대학교 산업시스템공학부

CHAPTER 6 AGGREGATE PLANNING AND INVENTORY MANAGEMENT 명지대학교 산업시스템공학부 Learning Objectives You should be able to: Describe the hierarchical operations planning process in terms of materials planning & capacity

### Glossary of Inventory Management Terms

Glossary of Inventory Management Terms ABC analysis also called Pareto analysis or the rule of 80/20, is a way of categorizing inventory items into different types depending on value and use Aggregate

### STOCHASTIC SERVICE NETWORK DESIGN: THE IMPORTANCE OF TAKING UNCERTAINTY INTO ACCOUNT

Advanced OR and AI Methods in Transportation STOCHASTIC SERVICE NETWORK DESIGN: THE IMPORTANCE OF TAKING UNCERTAINTY INTO ACCOUNT Arnt-Gunnar LIUM, Stein W. WALLACE, Teodor Gabriel CRAINIC Abstract. The

### MATERIALS MANAGEMENT. Module 9 July 22, 2014

MATERIALS MANAGEMENT Module 9 July 22, 2014 Inventories and their Management Inventories =? New Car Inventory Sitting in Parking Lots Types of Inventory 1. Materials A. Raw material B. WIP C. Finished

### A Stochastic Inventory Placement Model for a Multi-echelon Seasonal Product Supply Chain with Multiple Retailers

The Sixth International Symposium on Operations Research and Its Applications (ISORA 06) Xinjiang, China, August 8 12, 2006 Copyright 2006 ORSC & APORC pp. 247 257 A Stochastic Inventory Placement Model

### Supply Chain Planning Considering the Production of Defective Products

Supply Chain Planning Considering the Production of Defective Products Ferrara Miguel, Corsano Gabriela, Montagna Marcelo INGAR Instituto de Desarrollo y Diseño CONICET-UTN Avellaneda 3657, Santa Fe, Argentina

### Case study of a batch-production/inventory system E.M.M. Winands 1, A.G. de Kok 2 and C. Timpe 3

Case study of a batch-production/inventory system E.M.M. Winands 1, A.G. de Kok 2 and C. Timpe 3 The plant of BASF under consideration consists of multiple parallel production lines, which produce multiple

### SINGLE-STAGE MULTI-PRODUCT PRODUCTION AND INVENTORY SYSTEMS: AN ITERATIVE ALGORITHM BASED ON DYNAMIC SCHEDULING AND FIXED PITCH PRODUCTION

SIGLE-STAGE MULTI-PRODUCT PRODUCTIO AD IVETORY SYSTEMS: A ITERATIVE ALGORITHM BASED O DYAMIC SCHEDULIG AD FIXED PITCH PRODUCTIO Euclydes da Cunha eto ational Institute of Technology Rio de Janeiro, RJ

### We consider a single-product inventory system that serves multiple demand classes, which differ in their

MANAGEMENT SCIENCE Vol. 53, No. 9, September 2007, pp. 1486 1500 issn 0025-1909 eissn 1526-5501 07 5309 1486 informs doi 10.1287/mnsc.1070.0701 2007 INFORMS A Single-Product Inventory Model for Multiple

### Optimizing Strategic Safety Stock Placement in Supply Chains. Stephen C. Graves Sean P. Willems

Optimizing Strategic Safety Stock Placement in Supply Chains Stephen C. Graves Sean P. Willems Leaders for Manufacturing Program and A. P. Sloan School of Management Massachusetts Institute of Technology

### Research Article An Optimal Returned Policy for a Reverse Logistics Inventory Model with Backorders

Advances in Decision Sciences Volume 212, Article ID 386598, 21 pages doi:1.1155/212/386598 Research Article An Optimal Returned Policy for a Reverse Logistics Inventory Model with Backorders S. R. Singh

### A Theoretical Game Approach for Two- Echelon Stochastic Inventory System

Acta Polytechnica Hungarica Vol. 12, No. 4, 2015 A Theoretical Game Approach for Two- Echelon Stochastic Inventory System Saeed Alaei 1, Alireza Hajji 2, Reza Alaei 2, Masoud Behravesh 3* 1 Department

### Fundamentals of Operations Research. Prof. G. Srinivasan. Department of Management Studies. Indian Institute of Technology, Madras. Lecture No.

Fundamentals of Operations Research Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras Lecture No. # 22 Inventory Models - Discount Models, Constrained Inventory

### A Cross-Functional View of Inventory Management, Why Collaboration among Marketing, Finance/Accounting and Operations Management is Necessary

A Cross-Functional View of Inventory Management, Why Collaboration among Marketing, Finance/Accounting and Operations Management is Necessary Richard E. Crandall, Appalachian State University, John A.

### Optimal and Heuristic Echelon ( r, nq, T ) Policies in Serial Inventory Systems with Fixed Costs

OPERATIONS RESEARCH Vol. 58, No. 2, March April 2010, pp. 414 427 issn 0030-364X eissn 1526-5463 10 5802 0414 informs doi 10.1287/opre.1090.0734 2010 INFORMS Optimal and Heuristic Echelon ( r, nq, T )

### Universidad del Turabo MANA 705 DL Workshop Eight W8_8_3 Aggregate Planning, Material Requirement Planning, and Capacity Planning

Aggregate, Material Requirement, and Capacity Topic: Aggregate, Material Requirement, and Capacity Slide 1 Welcome to Workshop Eight presentation: Aggregate planning, material requirement planning, and

### Key Concepts: Week 5 Lesson 3: Economic Order Quantity (EOQ) Extensions

Key Concepts: Week 5 Lesson 3: Economic Order Quantity (EOQ) Extensions Learning Objectives Understand impact of a non- zero deterministic lead time on EOQ Understand how to determine the EOQ with different

### Simulation-based Optimization Approach to Clinical Trial Supply Chain Management

20 th European Symposium on Computer Aided Process Engineering ESCAPE20 S. Pierucci and G. Buzzi Ferraris (Editors) 2010 Elsevier B.V. All rights reserved. Simulation-based Optimization Approach to Clinical

### Development of a decision support tool for supply network planning: A case study from the chemical industry

The 7th International Symposium on Operations Research and Its Applications (ISORA 08) Lijiang, China, October 31 Novemver 3, 2008 Copyright 2008 ORSC & APORC, pp. 18 24 Development of a decision support

### 2.1 Model Development: Economic Order Quantity (EOQ) Model

_ EOQ Model The first model we will present is called the economic order quantity (EOQ) model. This model is studied first owing to its simplicity. Simplicity and restrictive modeling assumptions usually

### Final Report. to the. Center for Multimodal Solutions for Congestion Mitigation (CMS) CMS Project Number: 2010-018

Final Report to the Center for Multimodal Solutions for Congestion Mitigation (CMS) CMS Project Number: 2010-018 CMS Project Title: Impacts of Efficient Transportation Capacity Utilization via Multi-Product

### Ud Understanding di inventory issues

Lecture 10: Inventory Management Ud Understanding di inventory issues Definition of inventory Types of inventory Functions of inventory Costs of holding inventory Introduction to inventory management Economic

### Retailer's inventory system in a two-level trade credit financing with selling price discount and partial order cancellations

Thangam Journal of Industrial Engineering International 014, 10:3 ORIGINAL RESEARCH Open Access Retailer's inventory system in a two-level trade credit financing with selling price discount and partial

### A Programme Implementation of Several Inventory Control Algorithms

BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume, No Sofia 20 A Programme Implementation of Several Inventory Control Algorithms Vladimir Monov, Tasho Tashev Institute of Information

### Joint Location-Two-Echelon-Inventory Supply chain Model with Stochastic Demand

Joint Location-Two-Echelon-Inventory Supply chain Model with Stochastic Demand Malek Abu Alhaj, Ali Diabat Department of Engineering Systems and Management, Masdar Institute, Abu Dhabi, UAE P.O. Box: 54224.

### Basic Concepts in Inventory Management

Basic Concepts in Inventory Management 2 Abstract In this chapter, the concept of inventory is discussed which is central to materials management function. The definition of inventory and various types

### A LOT-SIZING PROBLEM WITH TIME VARIATION IMPACT IN CLOSED-LOOP SUPPLY CHAINS

A LOT-SIZING PROBLEM WITH TIME VARIATION IMPACT IN CLOSED-LOOP SUPPLY CHAINS Aya Ishigaki*, ishigaki@rs.noda.tus.ac.jp; Tokyo University of Science, Japan Tetsuo Yamada, tyamada@uec.ac.jp; The University

### In the supply-chain literature, an increasing body of work studies how suppliers can use

A Supplier s Optimal Quantity Discount Policy Under Asymmetric Information Charles J Corbett Xavier de Groote The Anderson School at UCLA 110 Westwood Plaza Box 951481 Los Angeles California 90095-1481

### Strategic Framework to Analyze Supply Chains

Strategic Framework to Analyze Supply Chains 1 Andy Guo A Strategic Framework for Supply Chain Design, Planning, and Operation Part I: Understand the supply chain Part II: Supply chain performance Part

### Single item inventory control under periodic review and a minimum order quantity

Single item inventory control under periodic review and a minimum order quantity G. P. Kiesmüller, A.G. de Kok, S. Dabia Faculty of Technology Management, Technische Universiteit Eindhoven, P.O. Box 513,

### Inventory Theory 935

19 Inventory Theory Sorry, we re out of that item. How often have you heard that during shopping trips? In many of these cases, what you have encountered are stores that aren t doing a very good job of

### The impact of order variance amplification/dampening on supply chain performance

Faculty of Economics and Applied Economics The impact of order variance amplification/dampening on supply chain performance Robert N. Boute, Stephen M. Disney, Marc R. Lambrecht and Benny van Houdt DEPARTMENT

### Inventory basics. 35A00210 Operations Management. Lecture 12 Inventory management. Why do companies use inventories? Think about a Siwa store

35A00210 Operations Management Lecture 12 Inventory management Lecture 12 Inventory management Inventory basics Inventory basics Pros and cons of inventory Inventory numbers Inventory management in practice

### By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

Copyright 214 IEEE. Reprinted, with permission, from Maryam Hamidi, Haitao Liao and Ferenc Szidarovszky, A Game-Theoretic Model for Outsourcing Maintenance Services, 214 Reliability and Maintainability