Practical Assignment Optimization: Waste Collection. Roel Wijgers, MSc 21 November 2011

Transcription

1 Practical Assignment Optimization: Waste Collection Roel Wijgers, MSc

2 Profile CQM Specialists in fact-based design and improvement of industrial, administrative and logisic processes Focus on Planning Logistics Process improvement Our basis Our company Six sigma Optimization Logistic models 30 consultants, 30 years experience Company completely owned by management and employees Located in Eindhoven 2

3 Practical assignment: AVR - Van Gansewinkel Offers integral waste services and reliable environmental solutions for 8 European countries Specialized in collecting, transferring, recycling and processing waste 3

4 Practical assignment in a nutshell Given the following inputs: A list of orders of waste collection points A distance matrix between waste collection points A number of waste collection vehicles A waste disposal location Create the following plan: Create a weekly schedule for each vehicle such that as much orders as possible are fulfilled and the total use time of the waste collection vehicles is minimized 4

5 Orders AVR Van Gansewinkel AVR Van Gansewinkel has various subscription types for sale for the collection of waste: Fixed schedule for customers - Frequency varies from five times per week to once every 12 weeks. For this assignment the frequency varies from one to five times per week. One ore more containers with a volume of 140 to 5000 liters 5

6 Valid frequencies for waste collection When a customer subscribes for example for garbage collection twice per week, the two collection times should be more or less evenly spread over the week Table below shows valid waste collection patterns Indication Frequency Valid patterns 1PWK Once per week mo, tu, we, th, fr 2PWK Twice per week mo_th, tu_fr 3PWK Three times per week mo_we_fr 4PWK Four times per week mo_tu_we_th, mo_tu_we_fr, mo_tu_th_fr, mo_we_th_fr, tu_we_th_fr 5PWK Five times per week mo_tu_we_th_fr 6

7 Fleet AVR Van Gansewinkel 2 vehicles Both vehicles available on Monday to Friday from 6:00h until 18:00h Outside the times above the vehicles have to be empty and be present at the waste disposal location The capacity per vehicle is liters The volume of waste is reduced by a factor five when it is collected (a container of 1000 liters corresponds with a volume of 200 liter in the garbage collection vehicle) - Containers usually are not completely filled - Waste is thickened by compressing it 7

8 Disposal of waste Collected waste has to be taken to the waste processor which is located at the waste disposal location Disposal of waste always takes 30 minutes It is allowed to dispose waste more than once per day The two vehicles may dispose waste at the same time When waste is disposed at the end of the day, the waste disposal has to be finished before 18:00h 8

9 Main goal of assignment Make routes whereby for each customer the waste is collected with the agreed frequency The total use time of the vehicles has to be minimized. The total use time is the sum of: - Time of emptying containers - Total travel time - Time of disposing waste Orders have to be planned completely or not be planned: - Not planning an order yields a penalty of 3 times the total emptying time. The total emptying time is defined as the single emptying time multiplied by the number of times an order has to be collected. 9

10 Datasets Orderbestand.txt Order Plaats Frequentie AantContainers VolumePerContainer LedigingsDuurMinuten MatrixID Xcoordinaat Ycoordinaat Unique number for the order Location Collection frequency of the order Number of containers that have to be collected each time. All containers have the same type (volume) Volume per container at the customer Emptying time of this order (all containers together) Reference to the distance matrix X coordinate of this order Y coordinate of this order AfstandenMatrix.txt MatrixID1 MatrixID2 Afstand Rijtijd Reference of the from location Reference of the to location Distance from the from location to the to location in meters Travel time from the from location to the to location in seconds 10

11 Format solution A route is a per vehicle (1 and 2) per day (1 through 5) ordered list of orders that are collected after each other. The route also contains one or more waste disposal moments. Format file: Vehicle; Day; Sequence number; Order Vehicle {1, 2} Day {1,, 5} (1=mo, 2=tu, 3=we, 4=th, 5=fr) Sequence number Order {1, 2, } Sequence number from which the sequence of the route per vehicle per day can be deduced. The sequence may start per vehicle each day at 1. Order from Orderbestand.txt. When the vehicle goes to dispose waste, this should be indicated with order number 0. 11

12 Waste disposal location AVR Van Gansewinkel Oost Brabant Den Engelsman 4 Maarheeze MatrixID =

13 Omitted conditions In the project CQM executed for AVR Van Gansewinkel the following conditions also had to be taken into account: Continuity for the customer (collect garbage at the approximately the same time each day) Continuity for the driver (each day more or less the same addresses, whereby some addresses are deleted or added) Additional frequencies for orders Different waste disposal locations with various disposal time and costs Fuel costs Vehicles are not homogeneous 13

14 Results project Saving in costs Saving in kilometres Saving in planning time - At first a full time planner was required for about 3 to 4 months, this has been reduced to approximately one month More insight in the effects of new customers 14

15 Questions 15

16 Information about CQM 16

17 Nacht van Eindhoven Competition between universities organized by CQM Team from University Utrecht won the 2008 edition: - Wilke van der Schee, Bas den Heijer en Bart Janssen 17

18 Profile CQM Specialists in fact-based design and improvement of industrial, administrative and logisic processes Focus on Planning Logistics Process improvement Our basis Our company Six sigma Optimization Logistic models 30 consultants, 30 years experience Company completely owned by management and employees Located in Eindhoven 18

19 Employees and partners Mathematicians, econometricians, and computer scientists: 15 PhDs 15 MA/MSc s 19

20 Areas of expertise Process Improvement Six Sigma Product and process design Design for Six Sigma Logistic and traffic networks Network design and analysis Transport, maintenance, supply chain Planning 20

21 References 21

22 References 22

23 Plan.cqm.nl: Rebuild of Google Maps Mainly used as a service for developpers Very fast huge distance-matrix calculations 23

24 Inter modal planner Tailor made tool for various logistic partners Currently CQM takes part in European project to develop inter modal standard 24

25 Process improvement - 6sigma Problem Throughput times too large Quality is insufficient Yields are too low Logistic costs are too high.. Improved efficiency of processes Insight into critical mechanisms and parameters Better controlled processes Trained green & black belts Process improvement Focus on result Awareness Training Coaching in projects Result Approach 25

26 Product design Philishave - Philips DAP Optimize the design of the Philishave CTQs closeness and irritation within confidence limits Variance of the process under control Problem DFSS Optimal design: Fact-based for tolerances of critical design parameters Collection of designs that pass the CTQ demands Design robust for process variance Qualitative model te determine critical design parameters Quantitative model for relation between CTQs and design parameters Model-based tolerancing Result Approach 26

27 LOT - DHL Transport planning Problem Quantification of synergy advantage Automated planning orders a week Transport planning Develop Linehaul optimization tool (Lot) Schedule for packet streams in Europa Huge network Multimodal transport Dock allocation, transfer Analysis and specification phase Software implementation Training and implementation in organisation Result Approach 27

28 Optirail - ProRail Maintenance planning Tension usage vs. maintenance Maximize rest capacity Problem Create maintenance planning voor long term (years) Achieved: Insight of effect maintenance on capacity After implementation: Saving in planning time Higher rest capacity Balanced planning Maintenance planning Grouping of activities Network algorithms Capacity calculation Research part in cooperation with University of Tilburg Result Approach 28

29 Design of logistic network For a lot of customers the ideal organization of the logistic network has been established. Supply Chain planning Design and improvement of the logistic network w.r.t. Warehouse locations, Production options Supply concepts Take into account: Transport, warehouse and stocking costs Requirements delivery Development of innovative planning logic in cooperation with TU/e Implement interactive planning software Development of new planning process Problem Result Approach 29