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Thesis (M.S.)--Ohio University, November, 2002. / Title from PDF t.p.

Many high-volume warehouses for small parts such as pharmaceuticals, cosmetics and office supplies seek to improve efficiency by creating forward pick areas in which many popular products are stored in a small area that is replenished from reserve storage. This thesis addresses the question of how to stock forward pick areas to maximum benefit by answering two key, inter-related decisions that have been called Assignment-Allocation. The assignment question asks which SKUs should be stored in the forward pick area? And the allocation question asks how much space should be allocated to each SKU? We show fast, simple, near-optimal algorithms to answer these questions in a variety of circumstances. To allocate space to SKUS, we introduce a Powers of Two allocation scheme designed to simplify shelf management. In addition, we present a ranking-based algorithm to assign SKUs and allocate space among multiple forward pick areas. We show that a similar algorithm that accounts for constraints on congestion and workload within the forward pick area. We also show how to determine the optimal assignment for warehouses with one or more forward pick areas that allocate space in ways that are common in practice. Warehouses frequently use the 80-20 rule to manage SKUs based on their popularity. We examine empirical data from thirty warehouses and analyze whether the power law distribution is a suitable fit. We test the hypothesis that the power law fits of warehouses in similar industries are themselves similar. We review explanations for why power laws arise in other settings and identify those that are plausible in the warehouse setting.

Automated storage and Retrieval (AS/R) systems have had a significant impact on storage and retrieval of finished goods, work-in-process, and raw materials and supplies. A microcomputer-based simulation model was developed to evaluate different unit load AS/R systems serving multiple input sources and output destinations. The simulation results were statistically analyzed on different performance measures including throughput, mean waiting times maximum waiting times and rejects. The results showed that for single-dock, square-in-time layouts, the class based arrangement produced significantly higher throughput for all scheduling policies. Among the scheduling policies, the relief nearest neighbor produced consistently higher throughput. Comparing square-in-time versus non-square-in-time layouts, the square-in-time layout performance was better; the performance deteriorated as deviations from square-in-time increased. For the two dual-dock layouts, at lower arrival rates the dedicated layout produced higher throughput; there was no significant difference between the two layouts at higher arrival rates. / Graduation date: 1992

Thesis (MSc)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: Order picking is the most important activity in distribution centres. It involves the process of retrieving products from storage in response to a speci c customer request. The order picking system in a distribution centre used by Pep Stores Ltd. (Pep), located in Durban, South Africa, is considered. The order picking system in Pep utilises picking lines. The system requires that the pickers move in a clockwise direction around the picking line. The planning of picking lines may be divided into three tiers of decisions. The rst tier determines which Stock Keeping Units (SKUs) should be allocated to which picking line and is known as the SKU to Picking Line Assignment Problem (SPLAP). The second tier, the SKU Location Problem (SLP), considers the positioning of the various SKUs in a picking line. The nal tier considers the sequencing of the orders for pickers within a picking line and is referred to as the Order Sequencing Problem (OSP). Collectively, these three tiers aim to achieve the objective of picking all the SKUs for all the orders in the shortest possible time. The decisions associated with each tier are made sequentially during the planning of a picking line. Each problem therefore relies on the information generated by its predecessing tier(s). Initially the OSP is addressed. A number of heuristic and metaheuristic approaches are presented, together with an exact formulation to solve this tier. The size of the problem is reduced by using a relaxation of the problem that may be solved exactly. A number of greedy tour construction heuristics, a scope and ranking algorithm, methods based on awarding starting locations with respect to preference ratios and a modi ed assignment approach was used to solve the OSP. Furthermore, a tabu search, simulated annealing, genetic algorithm and a generalised extremal optimisation approach are used to solve the OSP. The solution quality and computational times of all the approaches are compared for the data provided by Pep, with the generalised extremal optimisation approach delivering the best solution quality. Two methods from the literature was used to model the SLP, whereafter an ant colony system was used to maximise the number of orders in common between adjacent SKUs. A number of agglomerative clustering algorithms were used from which dendrograms could be constructed. Two novel heuristic clustering algorithms were considered. The rst heuristic calculates a distance between two clusters as the set of orders that have to collect all the SKUs in both clusters, whereas the second method is based upon the frequency of SKUs within a cluster. Little or no improvement was achieved in most cases. The SPLAP was introduced by means of a number of possibilities of how to formulate objectives. A possible exact formulation is presented, followed by a nearest neighbour search, which was initially used to construct new picking lines based on all data sets. A di erent approach was then taken by means of a tabu search where the waves of two or three picking lines were altered. Signi cant savings may be incurred for large data sets. / AFRIKAANSE OPSOMMING: Die opmaak van bestellings is die belangrikste aktiwiteit in 'n distribusiesentrum. Dit behels dat geskikte hoeveelhede produkte uit stoorplekke opgespoor en herpak moet word om aan kleinhandeltakke gestuur te word. Die bedrywighede binne een van Pep Stores Ltd. (Pep) se distribusiesentrums in Durban, Suid-Afrika, word beskou. Die sisteem vereis dat die werkers in 'n kloksgewyse rigting om 'n uitsoeklyn beweeg. Die beplanning van die uitsoeklyne kan verdeel word in drie besluite/probleme. Die eerste besluit is watter voorraadeenhede (VEs) toegewys moet word aan watter uitsoeklyn. Die tweede besluit is in watter vakkies in die uitsoeklyn die VEs geplaas moet word, en word die VE-plasings probleem (VLP) genoem. Die nale besluit is in watter volgorde bestellings opgemaak moet word in 'n uitsoeklyn, en staan bekend as die volgorde-van-bestellings-probleem (VBP). Die doel van al drie hierdie probleme is om al die bestellings in 'n uitsoeklyn in die kortste moontlike tyd af te handel. Die besluite wat verband hou met elke vlak van besluit word opeenvolgend gedoen tydens die beplanning van 'n uitsoeklyn. Die oplossing van elke subprobleem berus op die inligting van die voorafgaande probleme. Aanvanlik word die VBP beskou. 'n Aantal heuristiese en metaheuristiese benaderings word aangebied saam met 'n eksakte formulering om die derde vlak op te los. Die grootte van die probleem is verminder deur die gebruik van 'n verslapping van 'n eksakte formulering. 'n Aantal toerkonstruksie heuristieke, 'n omvang en rangorde algoritme, metodes wat gebaseer is op die toekenning van beginpunte met betrekking tot voorkeurverhoudings en 'n veralgemeende toewysingsprobleem is gebruik om die VBP op te los. 'n Tabu-soektog, gesimuleerde tempering, genetiese algoritme en 'n veralgemeende-ekstreme-optimering-benadering word ook gebruik om die VBP op te los. Die oplossingsgehalte en berekeningstye van al die benaderings word vergelyk vir werklike data wat verskaf is deur Pep. Die veralgemeende-ekstreme-optimering-benadering lewer die beste oplossingsgehalte. Twee metodes uit die literatuur is gebruik om die VLP te modelleer, waarna 'n mier kolonie stelsel gebruik word om die aantal bestellings wat aangrensende VEs in gemeen het te maksimeer. 'n Aantal groeperingsalgoritmes word gebruik wat dendrogramme kan lewer. Twee heuristiese groeperingsalgoritmes word oorweeg. Die eerste heuristiek bereken die afstand tussen twee groepe as die aantal bestellings wat al die VEs in beide groepe moet versamel, terwyl die tweede metode gebaseer is op die frekwensie van VEs binne 'n groep. Min of geen verbeterings is in die meeste gevalle gevind. Die eerste besluit word bekend gestel na aanleiding van 'n aantal moontlike maniere om die doelwitte te formuleer. 'n Moontlike eksakte formulering word aangebied. 'n Alternatiewe benadering is geneem deur middel van 'n tabu-soektog waar die golwe van twee of drie uitsoeklyne gewysig word. Beduidende besparings word gerealiseer vir groot datastelle.

This research is devoted to the development of a mathematical model for an Interleaving Warehouse Layout. The space allocated to the items in the warehouse is most commonly determined on the basis of inventory cost of the items. Once the space requirements for the items are computed, the actual assignment of items to locations in the warehouse is carried out independently. An Interleaving Warehouse Layout is presented in this research to incorporate both reorder quantity and location of each item in a single comprehensive mathematical model of the warehouse. The advantage of this approach is that it considers the quantity and location problems encountered in a warehouse layout simultaneously. The mathematical model developed for the warehouse layout is optimized utilizing the computer code GRG2.5. The numerical results for two warehouses are summarized, discussed and compared with the data available in the literature. / M.S.

Thesis (MSc)--Stellenbosch University, 2012. / 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. / AFRIKAANSE OPSOMMING: 'n Stelsel vir die opmaak van bestellings in 'n distribusiesentrum van Pep Stores Bpk. in Durban, Suid-Afrika word beskou. Hierdie stelsel gebruik uitsoeklyne waarop bestellings in golwe opgemaak word. 'n Uitsoeklyn is 'n area met vakkies waarop pallette met voorraadeenhede gestoor kan word. Hierdie vakkies is rondom 'n voerband gerangskik. Die stelsel het ooreenkomste met die eenrigting carrousselstelsels wat in die literatuur voorkom, maar hierdie eenrigtingstelsels is nie algemeen nie. Voorraadeenhede moet aan 'n golf toegewys word wat in 'n uitsoeklyn gerangskik word, waarna werkers dan die bestellings in die betrokke golf opmaak. Die hele operasie van bestellings opmaak kan opgebreek word in drie vlakke van besluite met gepaardgaande subprobleme. Die eerste twee subprobleme wat 'n enkele uitsoeklyn beskou, word aangespreek. Die eerste subprobleem, naamlik die volgorde-van-bestellings-probleem (VBP) beskou die volgorde waarin bestellings opgemaak word. Die tweede probeem is die voorraadeenheidaan- vakkie-toewysingsprobleem (VVTP) en beskou die toewysings van voorraadeenhede aan vakkies in 'n uitsoeklyn vir 'n gegewe golf. 'n Sterk ondergrens vir die VBP is bepaal met behulp van die konsep van 'n maksimum snit. Hierdie ondergrens kan gebruik word om 'n toelaatbare oplossing te bepaal wat hoogstens 1 carrousselsiklus meer as die ondergrens het. Hierdie oplossings kan dinamies gebruik word en kan dus net so in die praktyk aangewend word. Vinniger oplossingstegnieke is egter nodig indien die VVTP opgelos moet word. Twee metaheuristiese metodes word dus voorgestel waarmee oplossings vir die VBP vinniger bepaal kan word. 'n Mierkolonie benadering is ontwikkel om die VVTP op te los. Verder is vier variasies van 'n hi erargiese groeperingsalgoritme ontwikkel om voorraadeenhede saam te groepeer op 'n uitsoeklyn. Drie metaheuristieke is aangewend om hierdie groepe in volgorde te rangskik. Al hierdie benaderings vaar beter as bekende metodes om voorraadeenhede op 'n carroussel te rankskik. Om die geldigheid van die aannames en die praktiese uitvoerbaarheid van die oplossings te toets, is 'n agent gebaseerde simulasie model gebou. Daar is bevind dat al die voorgestelde oplossings prakties implementeerbaar is en dat al die metodes verbeter op die huidige werkswyse in Pep. Verder kon vasgestel word die VBP belangriker as die VVTP vir Pep is omdat veel kleiner potensiele besparings met die VVTP moontlik is as met die VBP.