Browsing by Author "Matthews, Jason"

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    Aanpassing van grootte-mengsels tydens voorraadtoewysing in 'n kettingwinkel
    (LitNet, 2014-12) Thom, Elmien; Visagie, Stephan; Matthews, Jason
    Die toewysing van voorraad aan winkels is een van die belangrike prosesse in die bestuur van ’n kettingwinkel. In die klerebedryf behels toewysingsbesluite onder andere die bepaling van hoeveelhede van elke grootte (byvoorbeeld klein, medium en groot) wat aan elke winkel gestuur moet word. ’n Gevallestudie van hierdie probleem in Pep Stores Bpk. (PEP), een van die vernaamste kleinhandelaars in Suid-Afrika, word in hierdie artikel beskou. In PEP word produkte by fabrieke bestel maande voordat dit in die takke beskikbaar is. Vanaf die fabrieke word die produkte na hul distribusiesentra verskeep, van waar dit per pad na die onderskeie takke versprei word. Onderliggend aan die verspreidingsnetwerk is ’n beplanningsproses en ’n toewysingsproses. Tydens die beplanningsproses word daar voorlopige toewysingsbesluite geneem. Tydens die toewysingsproses, wanneer daar meer onlangse verkoopsdata beskikbaar is, word die aanvanklike beplanning aangepas en word daar finaal besluit hoeveel van elke produk en grootte aan elke tak gestuur sal word. In hierdie artikel word modelle ontwikkel wat gebruik kan word wanneer hierdie finale toewysingsbesluite geneem word. Die doelwit van die modelle poog om voorraad só toe te wys dat geen winkel te min of te veel voorraad van enige grootte ontvang nie. Vier modelle word aangebied waarin die verwagte voorraad-tekorte en -surplusse by die takke geminimeer word. Twee van die modelle is doelwitprogrammeringsmodelle. Die eerste doelwitprogrammeringsmodel word nie aanbeveel nie, aangesien die tweede model beter resultate lewer in ’n korter oplossingstyd. Die tweede doelwitprogrammeringsmodel lewer goeie resultate, maar die oplossingstyd is in party gevalle te lank. Daarom is twee verslappings van hierdie model ontwikkel met die oog op die vermindering van oplossingstyd. Hierdie twee modelle lewer bevredigende oplossingstye en toon ’n gemiddelde verbetering van tot 27% op PEP se huidige oplossing volgens die verskillende maatstawwe.
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    Assignment of stock keeping units to parallel unidirectional picking
    (SAIIE, 2015-05) Matthews, Jason; Visagie, Stephan E.
    An order picking system consisting of a number of parallel unidirectional picking lines is investigated. Stock keeping units (SKUs) that are grouped by product type into distributions (DBNs) are assigned daily to available picking lines. A mathematical programming formulation and its relaxations is presented. A greedy insertion and a greedy phased insertion are further introduced to obtain feasible results within usable computation times for all test cases. The walking distance of the pickers was shown to decrease by about 22 per cent compared with the current assignment approach. However, product handling and operational risk increases.
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    Order sequencing and SKU arrangement on a unidirectional picking line
    (Stellenbosch : Stellenbosch University, 2012-03) Matthews, Jason; Visagie, S. E.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics.
    ENGLISH ABSTRACT: An order picking operation in a distribution centre (DC) owned by Pep Stores Ltd, located in Durban, South Africa was considered. The order picking operation utilises picking lines and the concept of wave picking. A picking line is a central area with storage locations for pallet loads of stock keeping units (SKUs) around a conveyor belt. The system shows many similarities to unidirectional carousel systems found in literature, however, the unidirectional carousel system is not common. Sets of SKUs must be assigned to pick waves. The SKUs associated with a single wave are then arranged on a picking line after which pickers move in a clockwise direction around the conveyor belt to pick the orders. The entire order picking operation was broken into three tiers of decision making and three corresponding subproblems were identi ed. The rst two subproblems were investigated which focused on a single picking line. The rst subproblem called the order sequencing problem (OSP) considered the sequencing of orders for pickers and the second called the SKU location problem (SLP) the assignment of SKUs to locations in the picking line for a given wave. A tight lower bound was established for the OSP using the concept of a maximal cut. This lower bound was transformed into a feasible solution within 1 pick cycle of the lower bound. The solution was also shown to be robust and dynamic for use in practice. Faster solution times, however, were required for use in solution techniques for the SLP. Four variations of a greedy heuristic as well as two metaheuristic methods were therefore developed to solve the problem in shorter times. An ant colony approach was developed to solve the SLP. Furthermore, four variations of a hierarchical clustering algorithm were developed to cluster SKUs together on a picking line and three metaheuristic methods were developed to sequence these clusters. All the proposed approaches outperformed known methods for assigning locations to SKUs on a carousel. To test the validity of assumptions and assess the practicality of the proposed solutions an agent based simulation model was built. All proposed solutions were shown to be applicable in practice and the proposed solutions to both subporblems outperformed the current approaches by Pep. Furthermore, it was established that the OSP is a more important problem, in comparison to the SLP, for Pep to solve as limited savings can be achieved when solving the SLP.
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    Picking line data set A
    (2014-02-13) Visagie, Stephan E.; Matthews, Jason
    This is a data set of picking lines that can by used for the comparison of the performance of different algorithms
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    Picking line data set B
    (2014-02-27) Visagie, Stephan E; Matthews, Jason
    This is a data set of picking lines that can by used for the comparison of the performance of different algorithms on the order sequencing and SKU location problem
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    SKU assignment in a multiple picking line order picking system.
    (Stellenbosch : Stellenbosch University, 2015-12) Matthews, Jason; Visagie, Stephan; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics.
    ENGLISH ABSTRACT: An order picking system in a distribution center (DC) owned by Pep Stores Ltd. (PEP) is investigated. Twelve unidirectional picking lines situated in the center of the DC are used to process all piece picking. Each picking line consists of a number of locations situated in a cyclical formation around a central conveyor belt. Pickers walk in a clockwise direction around a conveyor belt picking stock for stores. The picking lines are managed in waves due to PEPs policy to push stock to stores. For each wave of picking a subset of released stock keeping units (SKUs) is selected and assigned to an available picking line. The physical stock is then brought to the assigned picking line before multiple pickers pick all the store requirements (or orders) de ned by the SKUs within that wave. Once all of the orders have been picked a new mutually exclusive set of SKUs, de ning a new wave, is brought to the picking line for picking. In this way picking lines function in parallel to and independently of each other. The order picking system is deconstructed into three decision tiers. Firstly at the start of each day SKUs are assigned to available picking lines which de nes the Picking Line Assignment Problem (PLAP). Once a set of SKUs has been assigned to a picking line each SKU is assigned a 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 each picker. This de nes the Order Sequencing Problem (OSP). The focus of this dissertation is on the rst two subproblems namely, the SLP and PLAP as the OSP has already been solved in a previous study. This picking line setup considered here has many similarities to carousel systems. Several heuristic approaches for arranging SKUs within carousel systems are adapted for use in this picking line environment. These heuristics are compared to two novel lower bound formulations as well as trivial lower bound to evaluate their performance. Both historical as well as generated problem instances are used to compare the relative performances of each heuristic. An average saving of 2% for large and 6.5% for medium sized problem instances is achieved if the best solution form the four heuristics is selected. Three goals are used when assigning SKUs to picking lines in the PLAP. Firstly walking distance should be reduced, secondly the number of small cartons produced should be minimal and nally the number of pallet movements required to 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 shown that by minimising the maximal cut within each picking line the total walking distance is reduced. A greedy phased insertion heuristic is introduced which minimised the maximal cut and therefore walking distance. Although the total walking distance was reduced by on average 22% compared to historical assignments the number of small cartons produced and the number of pallet movements required to populate some picking lines is undesirable. Four measures using SKU correlations are introduced and used within a phased greedy insertion framework. These measures reduce the number of small cartons produced with a marginal increase in 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 assignments with the number of small cartons produced within an acceptable range. However, the number of pallet movements required to populate some of the picking lines remains at an undesirable level. A nal picking line segmentation approach is introduced using a sequence of integer programming formulations. These formulations include capacity constraints which limit the total volume of stock (and therefore the number of pallet movements) assigned to any one picking line. This approach delivers individual picking lines that have a manageable number of pallet movements to populate all picking lines with stock. A nal hybrid approach is also introduced which switches between this segmentation approach and a correlations approached when appropriate. This results in a 15% reduction in walking distance compared to historical assignments while maintaining a good number of small cartons produced and improving on the historical assignments in terms of the number of pallet movements required to populate any one picking line with stock. The managers within the DC are responsible for doing both the SKU to picking line assignments as well as the SKU arrangements within each picking line. A new warehouse management system (WMS) is in the process of design and implementation. A proof of concept interface which illustrated how the approaches to both the SLP and PLAP can be implemented in the new WMS while still allowing for managerial exibility is therefore proposed.