Marc Salomon

Strategic Issues in Product Recovery Management

textabstractThis article examines strategic production and operations management issues in product recovery management (PRM). PRM encompasses the management of all used and discarded products, components, and materials for which a manufacturing company is legally, contractually, or otherwise responsible. The objective of PRM is to recover as much of the economic (and ecological) value of used and discarded products, components, and materials as reasonably possible, thereby reducing the ultimate quantities of waste to a minimum. This article also discusses the relevance of PRM to durable products manufacturers. It contains a categorization of PRM decisions. A case study based on the PRM system of a multinational copier manufacturer is presented to illustrate a set of specific production and operations management issues. The experiences of two other pro-active manufacturers (BMW and IBM) are also discussed

Decomposition of a Combined Inventory and Time Constrained Ship Routing Problem

In contrast to vehicle routing problems, little work has been done in ship routing and scheduling, although large benefits may be expected from improving this scheduling process. We will present a real ship planning problem, which is a combined inventory management problem anda routing problem with time windows. A fleet of ships transports a single product (ammonia) between production and consumption harbors. The quantities loaded and discharged are determined by the production rates of the harbors, possible stock levels, and the actual ship visiting the harbor. We describe the real problem and the underlying mathematical model. To decompose this model, we discuss some model adjustments. Then, the problem can be solved by a Dantzig Wolfe decomposition approach including both ship routing subproblems and inventory management subproblems. The overall problem is solved by branch-and-bound. Our computational results indicate that the proposed method works for the real planning problem.

Batching decisions: structure and models

Abstract Batching decisions are one of managements instruments to impact performance of goods-flow systems. There is a vast body of literature on analysis and modeling of batching. This paper aims to provide a structure for batching decisions that can help in positioning batching research and models with respect to issues pertinent to goods-flow management. The basis of the structure is a distinction of batching issues as related to three decision levels: (i) process choice/design, (ii) activity planning (aggregate planning and activity programming), and (iii) activity control. Furthermore, the paper discusses some often heard criticisms of batching analysis. The paper concludes with a little speculation of the authors on the future directions of batching research.

An (s, Q) inventory model with remanufacturing and disposal

textabstractIn this paper we analyse an (s, Q) inventory model in which used products can be remanufactured to new ones. We develop two approximations for the average costs and compare their performance with that of an approximation suggested by Muckstadt and Isaac. Next we extend the model with the option to dispose returned products and present a heuristic optimisation procedure which is checked with full enumeration.

Routing Trains through railway stations: model formulation and algorithms

In this paper we consider the problem of routing trains through railway stations. This problem occurs as a subproblem in a project which the authors are carrying out in cooperation with the Dutch railways. The project involves the analysis of future infrastructural capacity requirements in the Dutch railway network. Part of this project is the automatic generation and evaluation of timetables. To generate a timetable a hierarchical approach is followed: at the upper level in the hierarchy a tentative timetable is generated, taking into account the specific scheduling problems of the trains at the railway stations at an aggregate level. At the lower level in the hierarchy it is checked whether the tentative timetable is feasible with respect to the safety rules and the connection requirements at the stations. To carry out this consistency check, detailed schedules for the trains at the railway yards have to be generated. In this paper we present a mathematical model formulation for this detailed scheduling problem, based on the Node Packing Problem (NPP). Furthermore, we describe a solution procedure for the problem, based on a branch-and-cut approach. The approach is tested in an empirical study with data from the station of Zwolle in The Netherlands.

An investigation of lead-time effects in manufacturing/remanufacturing systems under simple PUSH and PULL control strategies

In this paper we extend the PUSH and PULL control strategies defined by van der Laan et al. (E.A. van der Laan, M. Salomon, R. Dekker, Production planning and inventory control for remanufacturable durable products, Working paper 9531/A, Econometric Institute, Erasmus University Rotterdam, The Netherlands, 1995) to evaluate numerically the effects of lead-time duration and lead-time variability on total expected costs in production/inventory systems with remanufacturing. Although both strategies are non-optimal, they are relatively easy to analyse numerically and, more importantly, they are actually used in practice. The most important outcomes of the study are, that for both control strategies: (i) manufacturing lead-times have a larger influence on system costs than remanufacturing lead-times; (ii) a larger remanufacturing lead-time may sometimes result in a cost decrease; and (iii) a larger variability in the manufacturing lead-time may sometimes result in a cost decrease.

Multi-level lot-sizing problem: Evaluation of a simulated-annealing heuristic

Abstract The multi-level lot-sizing problem (MLP) is the problem of determining production quantities in multi-stage production settings, such that the sum of set-up and holding costs is minimized. This type of problem is hard to solve to optimality thereby compelling one to use heuristic approaches. In this paper we investigate heuristics based on a stochastic search method. Experimental results concerning the quality and efficiency of these methods for the MLP are presented and compared to the quality and efficiency of heuristic methods which are based on applying single-level heuristics on a level-by-level basis.

A set partitioning heuristic for the generalized assignment problem

This paper discusses a heuristic for the generalized assignment problem (GAP). The objective of GAP is to minimize the costs of assigning J jobs to M capacity constrained machines, such that each job is assigned to exactly one machine. The problem is known to be NP-Hard, and it is hard from a computational point of view as well. The heuristic proposed here is based on column generation techniques, and yields both upper and lower bounds. On a set of relatively hard test problems the heuristic is able to find solutions that are on average within 0.13% from optimality.

LINEAR PROGRAMMING, SIMULATED ANNEALING AND TABU SEARCH HEURISTICS FOR LOTSIZING IN BOTTLENECK ASSEMBLY SYSTEMS

Multilevel lotsizing is one of the most challenging subjects in production planning, especially in the presence of capacity constraints. In this paper we investigate lotsizing heuristics for assembly production systems with a bottleneck. More specifically, we discuss heuristics based on Linear Programming (LP), and compare the performance of these heuristics with the performance of approaches based on simulated annealing and tabu search techniques.A comparison of the three heuristics on a set of test problems shows that simulated annealing and tabu search perform well compared to pure LP-based heuristics, but the effectiveness of the latter heuristics can be improved by combining them with elements from simulated annealing and tabu search.

Solving the discrete lotsizing and scheduling problem with sequence dependent set-up costs and set-up times using the Travelling Salesman Problem with time windows

Abstract In this paper we consider the Discrete Lotsizing and Scheduling Problem with sequence dependent set-up costs and set-up times (DLSPSD). DLSPSD contains elements from lotsizing and from job scheduling, and is known to be NP-Hard. An exact solution procedure for DLSPSD is developed, based on a transformation of DLSPSD into a Travelling Salesman Problem with Time Windows (TSPTW). TSPTW is solved by a novel dynamic programming approach due to Dumas et al. (1993). The results of a computational study show that the algorithm is the first one capable of solving DLSPSD problems of moderate size to optimality with a reasonable computational effort.