The thesis deals with ways of increasing efficiency in retail with focus on logistics from theoretical as well as practical perspective. Application of the practical part is demonstrated on the example of Dotcom, online store project of Tesco Stores ČR a.s. First aim of the thesis is to identify areas with the biggest potential in increasing efficiency with respect to financial demands of the eventual investment and to propose a potential solution. Second aim is to verify a hypothesis that the delivery of goods to customers is inefficient given that the planning system is not being linked to the tracking system.

Background: With the exponential expansion of E-commerce, rising labor cost and higher customer expectations have pushed the implementation of advanced automation technology in warehouses. The order-picking-process is considered to be the most labor intensive and most expensive labor cost in warehouses. It has a crucial part to determine the lead time and customer satisfaction and because it is the last procedure before the order is shipped it can have negative effects on delivery quality, future customer relations and the overall satisfaction.  Purpose: The purpose of this paper is to evaluate how automation can help in the order picking process by studying the companies Shelfless and Exsitec to understand its effect on efficiency, cost and to understand the barriers and motivations to implementing it.  Method: This paper is based on a qualitative interview study with a deductive approach. The analysis method is based on within case analysis and cross-case analysis. Within case analysis is used to develop an understanding of each company to then later use a cross-case analysis to examine the difference between the two companies. Conclusion: The conclusion is that automation in the order picking process can increase the productivity whilst lowering the cost at the expense of a high installation fee with some disadvantages during the installation process like lower productivity, less flexibility. Although in the long run automation will be necessary to keep up with the growth of the companies.

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This research addresses decisions involved in the design of an order picking system in a distribution center. A distribution center (DC) in a logistics system is responsible for obtaining materials from different suppliers and assembling (or sorting) them to fulfill a number of different customer orders. Order picking, which is a key activity in a DC, refers to the operation through which items are retrieved from storage locations to fulfill customer orders. Several decisions are involved when designing an order picking system (OPS). Some of these decisions include the identification of the picking-area layout, configuration of the storage system, and determination of the storage policy, picking method, picking strategy, material handling system, pick-assist technology, etc. For a given set of these parameters, the best design depends on the objective function (e.g., maximizing throughout, minimizing cost, etc.) being optimized. The overall goal of this research is to develop a set of analytical models for OPS design. The idea is to help an OPS designer to identify the best performing alternatives out of a large number of possible alternatives. Such models will complement experienced-based or simulation-based approaches, with the goal of improving the efficiency and efficacy of the design process. In this dissertation we focus on the following two key OPS design issues: configuration of the storage system and selection between batch and zone order picking strategies. Several factors that affect these decisions are identified in this dissertation; a common factor amongst these being picker blocking. We first develop models to estimate picker blocking (Contribution 1) and use the picker blocking estimates in addressing the two OPS design issues, presented as Contributions 2 and 3. In Contribution 1 we develop analytical models using discrete-time Markov chains to estimate pick-face blocking in wide-aisle OPSs. Pick-face blocking refers to the blocking experienced by a picker at a pick-face when another picker is already picking at that pick-face. We observe that for the case when pickers may pick only one item at a pick-face, similar to in-the-aisle blocking, pick-face blocking first increases with an increase in pick-density and then decreases. Moreover, pick-face blocking increases with an increase in the number of pickers and pick to walk time ratio, while it decreases with an increase in the number of pick-faces. For the case when pickers may pick multiple items at a pick-face, pick-face blocking increases monotonically with an increase in the pick-density. These blocking estimates are used in addressing the two OPS design issues, which are presented as Contributions 2 and 3. In Contribution 2 we address the issue of configuring the storage system for order picking. A storage system, typically comprised of racks, is used to store pallet-loads of various stock keeping units (SKU) --- a SKU is a unique identifier of products or items that are stored in a DC. The design question we address is related to identifying the optimal height (i.e., number of storage levels), and thus length, of a one-pallet-deep storage system. We develop a cost-based optimization model in which the number of storage levels is the decision variable and satisfying system throughput is the constraint. The objective of the model is to minimize the system cost, which is comprised of the cost of labor and space. To estimate the cost of labor we first develop a travel-time model for a person-aboard storage/retrieval (S/R) machine performing Tchebyshev travel as it travels in the aisle. Then, using this travel-time model we estimate the throughput of each picker, which helps us estimate the number of pickers required to satisfy the system throughput for a given number of storage levels. An estimation of the cost of space is also modeled to complete the total cost model. Results from an experimental study suggest that a low (in height) and long (in length) storage system tends to be optimal for situations where there is a relatively low number of storage locations and a relatively high throughput requirement; this is in contrast with common industry perception of the higher the better. The primary reason for this contrast is because the industry does not consider picker blocking and vertical travel of the S/R machine. On the other hand, results from the same optimization model suggest that a manual OPS should, in almost all situations, employ a high (in height) and short (in length) storage system; a result that is consistent with industry practice. This consistency is expected as picker blocking and vertical travel, ignored in industry, are not a factor in a manual OPS. In Contribution 3 we address the issue of selecting between batch and zone picking strategies. A picking strategy defines the manner in which the pickers navigate the picking aisles of a storage area to pick the required items. Our aim is to help the designer in identifying the least expensive picking strategy to be employed that meets the system throughput requirements. Consequently, we develop a cost model to estimate the system cost of a picking system that employs either a batch or a zone picking strategy. System cost includes the cost of pickers, equipment, imbalance, sorting system, and packers. Although all elements are modeled, we highlight the development of models to estimate the cost of imbalance and sorting system. Imbalance cost refers to the cost of fulfilling the left-over items (in customer orders) due to workload-imbalance amongst pickers. To estimate the imbalance cost we develop order batching models, the solving of which helps in identifying the number of items unfulfilled. We also develop a comprehensive cost model to estimate the cost of an automated sorting system. To demonstrate the use of our models we present an illustrative example that compares a sort-while-pick batch picking system with a simultaneous zone picking system. To summarize, the overall goal of our research is to develop a set of analytical models to help the designer in designing order picking systems in a distribution center. In this research we focused on two key design issues and addressed them through analytical approaches. Our future research will focus on addressing other design issues and incorporating them in a decision support system. / Ph. D.

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.

Abstract  The purpose of the thesis was to investigate the order picking process for different sized items on different floors. The thesis purpose was also to study how the warehouse layout is affected by different sized items. The study also aimed to identify different ways to streamline order picking by optimizing the layout. To answer the research questions, qualitative studies were conducted where interviews and observations were used to investigate different activities on different floors of the case company. The result revealed the large items on different floors have a great impact on the layout as large items require special handling and can otherwise lead to inefficient picking times. By implementing restructuring of different items on the upper floor and implementing inventory systems such as ABC-analysis, the order picking process can be streamlined. This leads to reduced picking time as the picker doesn’t have to travel unnecessarily long distances. The result of this study can be useful for companies that work with large items and want to improve their order picking process. For further research, it is suggested to evaluate the proposed measures in practice. / Sammanfattning Examensarbetets syfte var att undersöka orderplockningsprocessen för olika stora artiklar på olika våningar samt hur lagerlayouten påverkas av artiklarnas storlek. Arbetet syftade också till att identifiera olika sätt att effektivisera orderplockningen genom att optimera layouten. För att besvara forskningsfrågorna genomfördes kvalitativa studier där intervjuer och observationer använts för att undersöka olika lageraktiviteter på olika våningar hos fallföretaget. Resultatet visade att stora artiklar på olika våningar har en stor påverkan på layouten eftersom de kräver en särskild hantering, vilket kan leda till ineffektiva plocktider. Genom att implementera omstrukturering av olika artiklar på övervåningen och implementera lagersystem som ABC-analys så kan orderplockningsprocessen effektiviseras. Detta leder till minskad plocktid genom att plockaren inte behöver färdas onödigt långa sträckor. Resultaten för denna studie kan vara nytta för företag som jobbar med stora artiklar och vill förbättra sin orderplockningsprocess. För ytterligare forskning så föreslås det att utvärdera de förslagna åtgärderna i praktiken.

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

Order-picking operations constitute the costliest activities in a warehouse. The order-picking problem (OPP) aims to determine the route of the picker(s) in such a way that the total order-picking time, hence the order-picking costs are minimized. In this study, a warehouse that consists of parallel pick aisles is assumed, and various versions of the OPP are considered. Although the single-picker version of the problem has been well studied in the literature, the multiple-picker version has not received much attention in terms of algorithmic approaches. The literature also does not take into account the time taken by the number of turns during the picking route. In this thesis, a detailed discussion is made regarding the computational complexity of the OPP with a single picker. A heuristic procedure, which makes use of the exact algorithm for the OPP with no middle aisles, is proposed for the single-picker OPP with middle aisles, and computational results on randomly generated problems are given. Additionally, an evolutionary algorithm that makes use of the cluster-first, route-second and route-first, cluster-second heuristics for the VRP is provided. The parameters of the algorithm are determined based on preliminary runs and the algorithm is also tested on randomly generated problems, with different weights given to the cluster-first, route-second and route-first, cluster-second approaches. Lastly, a polynomial time algorithm is proposed for the problem of minimizing the number of turns in a parallel-aisle warehouse.

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.