SKU assignment in a multiple picking line order picking system.

[摘要] ENGLISH ABSTRACT: An order picking system in a distribution center (DC) owned by Pep Stores Ltd. (PEP) isinvestigated. Twelve unidirectional picking lines situated in the center of the DC are used toprocess all piece picking. Each picking line consists of a number of locations situated in acyclical formation around a central conveyor belt. Pickers walk in a clockwise direction arounda conveyor belt picking stock for stores.The picking lines are managed in waves due to PEPs policy to push stock to stores. For eachwave of picking a subset of released stock keeping units (SKUs) is selected and assigned to anavailable picking line. The physical stock is then brought to the assigned picking line beforemultiple pickers pick all the store requirements (or orders) de ned by the SKUs within thatwave. Once all of the orders have been picked a new mutually exclusive set of SKUs, de ninga new wave, is brought to the picking line for picking. In this way picking lines function inparallel to and independently of each other.The order picking system is deconstructed into three decision tiers. Firstly at the start of eachday SKUs are assigned to available picking lines which de nes the Picking Line AssignmentProblem (PLAP). Once a set of SKUs has been assigned to a picking line each SKU is assigneda speci c location within the picking line which de nes the SKU Location Problem (SLP).Finally once pickers are brought to the picking line the individual orders are sequenced for eachpicker. This de nes the Order Sequencing Problem (OSP). The focus of this dissertation is ontherst two subproblems namely, the SLP and PLAP as the OSP has already been solved in aprevious study.This picking line setup considered here has many similarities to carousel systems. Severalheuristic approaches for arranging SKUs within carousel systems are adapted for use in thispicking line environment. These heuristics are compared to two novel lower bound formulationsas well as trivial lower bound to evaluate their performance. Both historical as well as generatedproblem instances are used to compare the relative performances of each heuristic. An averagesaving of 2% for large and 6.5% for medium sized problem instances is achieved if the bestsolution form the four heuristics is selected. Three goals are used when assigning SKUs topicking lines in the PLAP. Firstly walking distance should be reduced, secondly the number ofsmall cartons produced should be minimal andnally the number of pallet movements requiredto populate any one picking line for a wave of picking should be manageable.The concept of a maximal cut is used as an estimate for total walking distance and it is shownthat by minimising the maximal cut within each picking line the total walking distance isreduced. A greedy phased insertion heuristic is introduced which minimised the maximal cutand therefore walking distance. Although the total walking distance was reduced by on average22% compared to historical assignments the number of small cartons produced and the numberof pallet movements required to populate some picking lines is undesirable.Four measures using SKU correlations are introduced and used within a phased greedy insertionframework. These measures reduce the number of small cartons produced with a marginal increasein total walking distance compared to approaches which minimized the maximal cut only.The total walking distance is reduced by on average 20% compared to historical assignmentswith the number of small cartons produced within an acceptable range. However, the numberof pallet movements required to populate some of the picking lines remains at an undesirablelevel.Anal picking line segmentation approach is introduced using a sequence of integer programmingformulations. These formulations include capacity constraints which limit the total volumeof stock (and therefore the number of pallet movements) assigned to any one picking line. Thisapproach delivers individual picking lines that have a manageable number of pallet movementsto populate all picking lines with stock. Anal hybrid approach is also introduced whichswitches between this segmentation approach and a correlations approached when appropriate.This results in a 15% reduction in walking distance compared to historical assignments whilemaintaining a good number of small cartons produced and improving on the historical assignmentsin terms of the number of pallet movements required to populate any one picking linewith stock.The managers within the DC are responsible for doing both the SKU to picking line assignmentsas well as the SKU arrangements within each picking line. A new warehouse managementsystem (WMS) is in the process of design and implementation. A proof of concept interfacewhich illustrated how the approaches to both the SLP and PLAP can be implemented in thenew WMS while still allowing for managerial exibility is therefore proposed.

[发布机构] Stellenbosch University