Showing papers by "René de Koster published in 2012"

Determining the number of zones in a pick-and-sort order picking system

Abstract: In this study we consider a pick-and-sort order picking system, in which batches of orders are picked simultaneously from different (work) zones by a group of order pickers. After picking, the orders are transported by a conveyor to a next station for consolidation and packing. Packing can only occur when an order has been picked completely. For a given number of workers, each assigned to a single zone, a larger number of zones reduces pick time (since travel time reduces), but increases waiting time for completion at the packing stations, because more partial batches needing assembly arrive at the packing stations. Our aim is to determine the optimal number of zones such that the total (picking and packing) time to complete a batch is minimised. We solve this problem by optimally assigning items to pick routes in each zone. We illustrate the method with data taken from a distribution centre of one of the largest online retailers in The Netherlands.

Sequencing heuristics for storing and retrieving unit loads in 3D compact automated warehousing systems

Abstract: Sequencing unit-load retrieval requests has been extensively reported on in the literature for conventional single-deep automated warehousing systems. A proper sequence can greatly reduce the makespan when carrying out a group of such requests. Although the sequencing problem is NP-hard, some very good heuristics exist. Surprisingly, the problem has not yet been investigated for compact (multi-deep) storage systems, which have greatly increased in popularity the last decade. This article studies how to sequence a group (or block) of storage and retrieval requests in a multi-deep automated storage system with the objective to minimize the makespan. Currently utilized sequencing heuristics for the multi-deep system are adapted in this article and in addition a new heuristic, Percentage Priority to Retrievals with Shortest Leg (PPR-SL), is proposed and evaluated. It is shown that the PPR-SL heuristic consistently outperforms all of the other heuristics. Generally, it can outperform the benchmark First-Come F...

Optimal Design of Container Terminal Layout

Abstract: Due to rapid growth in foreign trade using sea vessels, there is a growing focus in improving the infrastructure and operational efficiencies at the container terminals. Particularly, the operational responsiveness of loading and unloading of containers, affects the vessel idle times and profitability of the shipping liners. In this research, we determine optimal stack layout design, which minimizes the container unload times using Automated Guided Vehicles (AGVs). To analyze alternate stack layout designs, we develop integrated queuing network models that capture the stochastic interactions among the container terminal processes (quayside, vehicle transport, and stackside), and provides realistic estimates of expected container unload throughput times. 1 Background and Motivation Due to growth in international trade and better accessibility to the major seaports via deep-sea vessels, containerization has become the preferred mode for maritime shipping and inland transportation. Between 1990 and 2008, container traffic has grown from 28.7 million TEU to 152.0 million TEU, an increase of about 430% ([3]). Currently, several new deep-sea as well as inland container terminals are being designed across continents. Several of the larger ones will be automated. The design of the container terminal includes strategic design choices such as the terminal layout at the stackside, choice of equipment for handling containers at the seaside and landside, and type of vehicles for container transport between seaside and the landside. However, the process to arrive at an optimal design is extremely

Toward Sustainability, High Density and Short Response Time by Live-cube Storage Systems

Abstract: This paper studies random storage in a live-cube storage system where loads are stored multi-deep. Although such storage systems are still rare, they are increasingly used, for example in automated car parking systems. Each load is accessible individually and can be moved to a lift on every level of the system in xand y-directions by a shuttle as long as an open slot is available next to it, comparable to Sam Loyd’s sliding puzzles. A lift moves the loads across different levels in z-direction. We derive the expected travel time of a random load from its storage location to the input/output point. We optimize system dimensions by minimizing the expected travel time.

Robust Design of Public Storage Warehouses

Abstract: We apply robust optimization and revenue management in public storage warehouses. We optimize the expected revenue of public storage warehouses against the worst cases with a max-min revenue objective, and the decision variables are mainly the number of storage units for each storage type. With the robust design, we can observe worst-case revenue improvement.

A Yard Crane Scheduling Problem with Practical Constraints

Abstract: The problem considered in this paper is to locate storage containers while a set of container storage and retrieval requests are sequenced. Two automated cranes stack and retrieve containers in a single block of a yard. The cranes cannot pass each other and must be separated by a safety distance. Storage containers are initially located at the seaside and landside input/output (I/O) points of the block. Each must be stacked in a specific location of the block, selected from a set of open locations suitable for stacking the storage container. Retrieval containers are initially located in the block and must be delivered to the I/O points. Due to the importance and acceptable waiting times of different modes of transport, requests have different priorities. The problem is modeled as a multiple asymmetric generalized traveling salesman problem with precedence constraints. The objective is to minimize the makespan. We have developed an adaptive large neighborhood search heuristic to quickly compute near-optimal solutions. The numerical experiments show that the solution method can obtain near-optimal solutions.