Batch picking in narrow-aisle order picking systems with consideration for picker blocking

This paper develops strategies to control picker blocking that challenge the traditional assumptions regarding the tradeoffs between wide- and narrow-aisle order picking systems. We propose an integrated batching and sequencing procedure called the indexed batching model (IBM), with the objective of minimizing the total retrieval time (the sum of travel time, pick time and congestion delays). The IBM differs from traditional batching formulations by assigning orders to indexed batches, whereby each batch corresponds to a position in the batch release sequence. We develop a mixed integer programming solution for exact control, and demonstrate a simulated annealing procedure to solve large practical problems. Our results indicate that the proposed approach achieves a 5–15% reduction in the total retrieval time primarily by reducing picker blocking. We conclude that the IBM is particularly effective in narrow-aisle picking systems.     

A travel time estimation model for a high-level picker-to-part system with class-based storage policies

Most previous related studies on warehouse configurations and operations only investigated single-level storage rack systems where the height of storage racks and the vertical movement of the picking operations are both not considered. However, in order to utilize the space efficiently, high-level storage systems are often used in warehouses in practice. This paper presents a travel time estimation model for a high-level picker-to-part system with the considerations of class-based storage policy and various routing policies. The results indicate that the proposed model appears to be sufficiently accurate for practical purposes. Furthermore, the effects of storage and routing policies on the travel time and the optimal warehouse layout are discussed in the paper.     

The impact of order batching and picking area zoning on order picking system performance

This paper proposes an approximation model based on queuing network theory to analyze the impact of order batching and picking area zoning on the mean order throughput time in a pick-and-pass order picking system. The model includes the sorting process needed to sort the batch again by order. Service times at pick zones are assumed to follow general distributions. The first and second moments of service times at zones and the visiting probability of a batch of orders to a pick zone are derived. Based on this information, the mean throughput time of an arbitrary order in the order picking system is obtained. Results from a real application and simulation show that this approximation model provides acceptable accuracy for practical purposes. Furthermore, the proposed method is simple and fast and can be easily applied in the design and selection process of order picking systems.     

A multicut L-shaped based algorithm to solve a stochastic programming model for the mobile facility routing and scheduling problem

This paper considers the mobile facility routing and scheduling problem with stochastic demand (MFRSPSD). The MFRSPSD simultaneously determines the route and schedule of a fleet of mobile facilities which serve customers with uncertain demand to minimize the total cost generated during the planning horizon. The problem is formulated as a two-stage stochastic programming model, in which the first stage decision deals with the temporal and spatial movement of MFs and the second stage handles how MFs serve customer demands. An algorithm based on the multicut version of the L-shaped method is proposed in which several lower bound inequalities are developed and incorporated into the master program. The computational results show that the algorithm yields a tighter lower bound and converges faster to the optimal solution. The result of a sensitivity analysis further indicates that in dealing with stochastic demand the two-stage stochastic programming approach has a distinctive advantage over the model considering only the average demand in terms of cost reduction.     

Two-worker blocking congestion model with walk speed m in a no-passing circular passage system

This paper introduces a blocking model and closed-form expression of two workers traveling with walk speed m (m = integer) in a no-passing circular-passage system of n stations and assuming n = m + 2, 2m + 2, …. We develop a Discrete-Timed Markov Chain (DTMC) model to capture the workers’ changes of walk, pick, and blocked states, and quantify the throughput loss from blocking congestion by deriving a steady state probability in a closed-form expression. We validate the model with a simulation study. Additional simulation comparisons show that the proposed throughput model gives a good approximation of a general-sized system of n stations (i.e., n > 2), a practical walk speed system of real number m (i.e., m ? 1), and a bucket brigade order picking application.     

A mixed integer programming model for long term capacity expansion planning: A case study from The Hunter Valley Coal Chain

The Hunter Valley Coal Chain is the largest coal export operation in the world with a throughput in excess of 100 million tonnes per annum (Mtpa). Coal is delivered to the shipping terminal from 40 mines using 27 coal load points spread across the Hunter Valley region. This paper describes an MILP model for determining the capacity requirements, and the most cost effective capacity improvement initiatives, to meet demand while minimising the total cost of infrastructure and demurrage. We present results from computational experiments on the model’s performance along with a comparison of the model’s output with detailed analyses by the coal chain analysts and planners.     

A simple plant-location model for quantity-setting firms subject to price uncertainty

The uncapacitated plant location problem under uncertainty is formulated in a mean-variance framework with prices in various markets correlated via their response to a common random factor. This formulation results in a mixed-integer quadratic programming problem. However, for a given integer solution, the resulting quadratic programming problem is amenable to a very simple solution procedure. The simplicity of this algorithm means that reasonably large problems should be solvable using existing branch-and-bound techniques.     

Mixed-width aisle configurations for order picking in distribution centers

Space required for the order picking area and labor required to perform the picking activity are two significant costs for a distribution center (DC). Traditionally, DCs employ either entirely wide or entirely narrow aisles in their picking systems. Wide aisles allow pickers to pass each other, which reduces blocking, and requires fewer pickers than their narrow-aisle counterpart for the same throughput. However, the amount of space required for wide-aisle configurations is high. Narrow aisles utilize less space than wide aisles, but are less efficient because of the increased likelihood of congestion experienced by pickers. We propose a variation to the traditional orthogonal aisle designs where both wide and narrow aisles are mixed within the configuration, with a view that mixed-width aisles may provide a compromise between space and labor. To analyze these new mixed-width aisle configurations, we develop analytical models for space and travel time considering randomized storage and traversal routing policies. Through a cost-based optimization model, we identify system parameters for which mixed-width aisle configurations are optimal. Experimental results indicate that annual cost savings of up to $48,000 can be realized over systems with pure wide or narrow aisle configurations.     

Defining order picking policy: A storage assignment model and a simulated annealing solution in AS/RS systems

Improving technology, variable customer demands, variety of products and increasing improvement of production systems has brought storage facilities, which has an important role on business operations, to a critical point. This circumstance has revealed the necessity on activating of storage systems and operations. In this study, mathematical model, which minimizes simultaneously storage allocation, storage retrieval and storage keeping costs, is generated for an AS/RS system of an enterprise. The mathematical model has run for small solution space and optimal solution is obtained. The problem in this study is an NP hard problem that is why optimal solution cannot be obtained for large solution spaces. So the problem in existing system is solved by using simulated annealing and an optimal order policy is proposed.     

Tabu search heuristics for the order batching problem in manual order picking systems

In a manual order picking system, order pickers walk or ride through a distribution warehouse in order to collect items requested by (internal or external) customers. In order to perform these operations efficiently, it is usually required that customer orders be combined into (more substantial) picking orders that are limited in size. The order batching problem considered in this paper deals with the question of how a given set of customer orders should be combined into picking orders such that the total length of all picker tours necessary for all of the requested items to be collected is minimized. For the solution of this problem the authors suggest two approaches based on the tabu search principle. The first is a (classic) tabu search (TS), and the second is the attribute-based hill climber (ABHC). In a series of extensive numerical experiments, these approaches are benchmarked against other solution methods put forward in the current literature. It is demonstrated that the proposed methods are superior to the existing methods and provide solutions which may allow distribution warehouses to operate more efficiently.     

Design and control of warehouse order picking: A literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for the warehouse, and consequently for the whole supply chain. In order to operate efficiently, the order-picking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.     

Improving product location and order picking activities in a distribution centre

This article examines the effect of different product location strategies on the distance that order pickers must cover to do their job. This distance is an important cost component in warehousing activities. Our empirical study is based on a real industrial setting, in which the products are located on both sides of a conveyor belt. We show that choosing the right product location strategy allows the current picking distance to be reduced more than 10%. We also propose a post-optimization procedure that can further reduce picking distances—up to 20% of the current distances. Through a study of the routing strategy used to dispatch pickers, we demonstrate that solving a simple travelling salesman problem can further reduce distances up to 13%, compared with the distances incurred using a predetermined route. We show that reductions of up to 27% compared to current picking distances are possible if our product location and routing methods are combined.     

Exact results for the order picking time distribution under return routing

This paper derives exact expressions for the Laplace-Stieltjes transform of the order picking time in single- and 2-block warehouses. We consider manual warehouses that deploy return routing and assume that order sizes follow a Poisson distribution. The results in this paper apply to a wide range of storage policies, including but not restricted to class-based and random storage. Furthermore, we compare the performance of the storage policies and warehouse lay-outs by using numerical inversion of the Laplace-Stieltjes transforms.     

An optimisation approach for the e-grocery order picking and delivery problem

Central European Journal of Operations Research - Traditional supermarket chains that are adopting an omni-channel approach must now carry out the order picking and delivery processes to serve...     

Branch and bound algorithm for a transfer line design problem: Stations with sequentially activated multi-spindle heads

In this paper, a new transfer line balancing problem is considered. The main difference from the simple assembly line balancing problem is that the operations are grouped into blocks (batches). All the operations of the same block are carried out simultaneously by one piece of equipment (multi-spindle head). Nevertheless, the blocks assigned to the same workstation are executed in series. The line cost consists of the sum of block and workstation costs. At the considered line design stage, the set of all available blocks is given. The aim is to find a subset from the given set of available blocks and to find a partition of this subset to workstations such that each operation is executed once and the line cost is minimal while all the precedence, cycle time, and compatibility (operation inclusion and block exclusion) constraints are respected. A new lower bound based on solving a special set partitioning problem is presented and a branch and bound algorithm is developed. The experimental results prove the quality of the lower bound and applicability of the suggested branch and bound algorithm for medium sized industrial cases.     

A five facets frame for the design of heuristics

The author suggested to distinguish between the ‘engineering approach’ and the ‘mathematical approach’ in connection with the design of heuristics. Stainton and Papoulias extended the scope by suggesting the ‘relational approach’. Based upon this extension, a five facets frame is presented here which is suggested to precede and accompany the ‘technical’ design of the heuristic. The facets are: coverage by participation, experience by doing, abstraction by structuring, extension by comparison, exploration by creativity.     

A graph-pair representation and MIP-model-based heuristic for the unequal-area facility layout problem

Owing to its theoretical as well as practical significance, the facility layout problem with unequal-area departments has been studied for several decades, with a wide range of heuristic and a few exact solution procedures developed by numerous researchers. In one of the exact procedures, the facility layout problem is formulated as a mixed-integer programming (MIP) model in which binary (0/1) variables are used to prevent departments from overlapping with one another. Obtaining an optimal solution to the MIP model is difficult, and currently only problems with a limited number of departments can be solved to optimality. Motivated by this situation, we developed a heuristic procedure which uses a “graph pair” to determine and manipulate the relative location of the departments in the layout. The graph-pair representation technique essentially eliminates the binary variables in the MIP model, which allows the heuristic to solve a large number of linear programming models to construct and improve the layout in a comparatively short period of time. The search procedure to improve the layout is driven by a simulated annealing algorithm. The effectiveness of the proposed graph-pair heuristic is demonstrated by comparing the results with those reported in recent papers. Possible extensions to the graph-pair representation technique are discussed at the end of the paper.     

Economic evaluation for the optimal introduction of flexible manufacturing technology under rivalry

Unless procedures for the economic evaluation of flexible manufacturing technology are revamped, much of U.S. industry could repeat the experience of American automobile and steel companies from the recent past. The dynamic character of flexible manufacturing technology in terms of associated developments in microelectronics, a trend toward equipment modularity, and the increasing diversity of relevant markets make flexible manufacturing especially vulnerable to the weaknesses of conventional procedures for the justification of capital expenditures. Building on the work of V. Smith, M.I. Kamien and N.L. Schwartz, this paper presents optimization models from which economically reasonable plans can be derived for the implementation of flexible manufacturing technology. Although the assumptions of these models are not focused on the situation of a specific plant, model implications and the overall perspectives here on the economic evaluation of flexible system options should provide general guidance for manufacturing planners.     

STaTS: A Slicing Tree and Tabu Search based heuristic for the unequal area facility layout problem

In this paper, a slicing tree based tabu search heuristic for the rectangular, continual plane facility layout problem (FLP) is presented. In addition to the incorporation of facilities with unequal areas we also integrate the possibility to specify various requirements regarding (rectangular) shape and dimensions of each individual facility by using bounding curves. Therefore, it is possible to solve problems containing facilities of fixed and facilities of flexible shapes at the same time. We present a procedure that calculates the layout corresponding to a given slicing tree on the basis of bounding curves. These layouts are slicing structures which are able to contain empty spaces to guarantee that stringent shape restrictions of facilities are kept. Due to these features this approach is better suited for practical use than so far existing ones. The effectiveness of our approach in terms of objective function value is shown by comparing our results to those found in the literature. Even a large problem instance comprised of 62 facilities has been solved.     

A survey for the quadratic assignment problem

The quadratic assignment problem (QAP), one of the most difficult problems in the NP-hard class, models many real-life problems in several areas such as facilities location, parallel and distributed computing, and combinatorial data analysis. Combinatorial optimization problems, such as the traveling salesman problem, maximal clique and graph partitioning can be formulated as a QAP. In this paper, we present some of the most important QAP formulations and classify them according to their mathematical sources. We also present a discussion on the theoretical resources used to define lower bounds for exact and heuristic algorithms. We then give a detailed discussion of the progress made in both exact and heuristic solution methods, including those formulated according to metaheuristic strategies. Finally, we analyze the contributions brought about by the study of different approaches.