A sugar distribution network: Designing and planning. Mehdi Sharifyazdi mehdis@chalmers.se



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Transcription:

A sugar distribution network: Designing and planning Mehdi Sharifyazdi mehdis@chalmers.se

Tale of a battle! Angry producers vs Naughty merchants

Agenda The problem Classification of provinces and customers Distribution channels/methods Refinement/Distribution/Storage planning

Demand 30 provinces 4 market segments Households Groceries Small local super markets Confectioneries/workshops Small industries Big industries (mostly soft drinks) Total demand 1300000-1500000 tons/year

Supply Khuzestan Domestic production Sugar cane SCDS: 350000 tons/year others Sugar beets Import

Supply SCDS Other SC producers Domestic suger beet prod. Import 30% 60% 3% 7%

Strategy To be independent of the merchants (partly) To have own distribution network Closer contact with final customers Bigger profit margin More competitiveness

Categorization of provinces Constructing sale regions Applying the same distribution method and organization for the provinces of the same region Utility : similar AND adjacent provinces in the same region

Steps Definition of indicators Data gathering Categorization algorithms Comparison of different categorizations

Indicators Density of demand points Distance to khuzestan Border points and ports Ratio of sale plan to demand Density of industrial demand points Density of sale plan in the market segments Density of demand in market segments Consumption pattern in market segments Density of railway network Density of road network Density of transportation companies Average road transport cost Density of sugar beet refineries Surface Demand Sale plan Geography/Demography Consumption and distribution pattern Transportation facilities, infrastructure and costs Facilities of sugar production and refinement Neighborhood Limits Similarity

Calculation of similarities Values of indicators for the provinces Giving weights to the indicators AHP Normalized similarity of the provinces m and n I mn wi 1 i a in a i a im ain w i a i Indicator i for the province n Weight of the indicator i Maximum gap between two provinces in the value of the indicator i

The first categorization algorithm Sort the provinces WRT demand density Most important indicator Construct the cores of the regions Add neighbor similar provinces to the cores until constraints are violated Demand density 1 2... s province

The second categorization algorithm Entry-to-entry multiplication of similarity and neighborhood matrices Diagonalization of the produced matrix Regions: blocks around the main diagonal Region 3 Region 2 Region 1 Region 4

Comparison of categorizations Generating new categorizations by interviews and exchanging provinces between neighbor regions Criterion of utility: average of average similarity of the provinces of the regions Ni 1 Ni 2 n j 1 k j 1 i 1 Ni i *( N n I jk 1) N i : number of provinces in region i n: number of provinces

Final regions 1 2 3 4 5 6 7

Choosing distribution methods Best distribution method for each (region,segment) Classification of 8 original market segments into 4 Data gathering in 7 sample cities for the 7 regions

Possible distribution methods/channels Distribution company Establishing a new one Contract with existing companies Via syndicates Direct sale Via agents Big Small Via merchants Keeping a part of current quota Distribute the rest by new methods Standards for distribution quota and storage capacity set according to: distribution power financial factors organizational needs reliability requirements Min quota Max quota

Procedure of choosing distribution methods Definition of comparison indicators Removal of infeasible methods w.r.t. limiting (constraint-like) indicators Making compensatable (objective-like) indicators independent: 21 initial indicators 14 independent indicators Giving weight to objective-like indicators Evaluation of each indicator for each (region,segment) Normalization and summarization of indicators Ranking distribution methods

Comparison indicators Class Indicator Compensatable /Limiting Distribution capacity Qualitative /Quantitative Lead time C Quantitative Flexibility of purchasing methods C Qualitative Closeness to final customer C Quantitative Effect on demand C Qualitative Applicability to the market segment L Qualitative Financial Investment return period Both Quantitative NPV Both Quantitative Initial investment needed C Quantitative Non-financial Compatibility with strategies L Qualitative Negative effects in the market C Qualitative Durability C Qualitative Effect on the bargaining power of the customers C Qualitative Needed organization C Qualitative

Results Market segment Region Households Workshops Small industries Big industries 1) North-west Direct sale Big agents Big agents 2) North Direct sale Big agents Big agents 3) Tehran Big agents Direct sale Big agents 4) North-east Via syndicates Big agents Direct sale Big agents 5) Centre Via syndicates Big agents Direct sale Big agents 6) South-west Big agents Direct sale Big agents 7) South-east Big agents Direct sale Big agents

Results

Planning of agents Decisions Number of small and big agents in each province Volume of sugar which agents of each province distribute In the same province In the other provinces of the region Objective: to minimize total transportation cost Based on road mode (trailers) Constraints Demand Total volume of sugar which can be distributed by the agents of a province Big agents: 150% of the demand : 120% of the demand A province may receive part of the needed sugar from other provinces Agents located in each province may be more than what is needed there

Refinement/Distribution/Storage planning B A Sugar cane farms/raw sugar factories B B Internal refineries Internal warehouses A External (sugar beet) refineries Intermediate warehouses Final customers

Decisions Location and capacity of intermediate warehouses The amount of sugar to be refined in external and internal refineries in each month of the year Inventory of raw and refined sugar at the end of each month, in all of the storage points of the network: [Internal] Warehouses of raw and refined sugar in Khuzestan Warehouses of the external refineries Intermediate warehouses of the company Warehouses of the agents The amount of transportation of raw and refined sugar among storage points of the network and the customers Customers: Receiving sugar from the warehouse of the agent (Group A) Receiving sugar without being stored in the agents (Group B)

Objective Minimize total cost: Annual capital cost of the intermediate warehouses Inventory holding cost at the internal (of the company in Khuzestan), external (refineries) and intermediate warehouses Cost of refining in external refineries Transportation cost of raw and refined sugar among storage point of the distribution network (factories in Khuzestan, external refineries, intermediate warehouses, agents and customers) Loading and unloading costs of sugar through the process of transportation

Constraints Capacity of production and storage Demand satisfaction (sale plan) Balance relations of inventory and transportation at storage points of the network Initial conditions (inventory) Solver: LINGO 8.0

What happened at the end? Sad ending: the distribution sub-company failed The merchants dominate the market Massive imports Dumping prices Tactical/Operational planning cannot work when strategy is poor