Heuristic Techniques for Simultaneous Scheduling of Production and Distribution in Multi-Echelon Structures: Theory and Empirical Comparisons

Abstract

Seven heuristic algorithms are discussed. Each can be used for production scheduling in an assembly network (a network where each work station has at most one immediate successor work station, but may have any number of immediate predecessor work stations), distribution scheduling in an arborescence network (a network where each warehouse or stocking point is supplied by at most one immediate predecessor stocking point, but may itself supply any number of immediate successor stocking points), and joint production-distribution scheduling in a conjoined assembly-arborescence network. The objective of each algorithm is to determine a production and/or product distribution schedule which satisfies final product demand and minimizes the sum of the average inventory holding costs and average fixed charges for processing (ordering, delivery, or setup costs), per period, over an infinite planning horizon. Exogenous demand for product is assumed to be deterministic, at a constant rate, and to occur only at "retail" facilities of the networks. On the basis of their performance in 11,000 computer generated problems, the seven heuristic methods are compared with each other and with a dynamic programming algorithm. The results indicate that for most of the network structures considered, the best heuristic is the method of steepest descent; the second best is a simple extension of a method originally developed by Crowston, Wagner, and Henshaw. The improved myopic procedure of Graves and Schwarz performs very well for some particular types of structures. Surprisingly, two particularly naive heuristics also perform quite well in certain situations. In addition to the computer simulation experiments, we also discuss a simple computer-compatible algebraic notation scheme for identifying structure (facility interrelationships) within networks of the three types considered.production/scheduling, inventory/production: deterministic models, marketing: distribution

An enhanced model for the integrated production and transportation problem in a multiple vehicles environment

“…William (1981) presented a simultaneous joint production-distribution scheduling, with the objective of minimizing the average inventory and operation cost in the supply chain. Cohen and Lee (1988) and Cohen and Moon (1991) proposed integrated production and distribution planning models to generate material requirement plans, production plans, and inventory and distribution plans.…”

On the integrated production, inventory, and distribution routing problem

“…In the literature, there are many known results available for either optimizing the inventory and distribution policies, or optimizing the production and inventory plans (e.g., see Williams (1981), Dror and Ball (1987), Goyal and Gupta (1989), Lee (1988, 1989), Blumenfeld, Burns and Dagunzo (1991), Anily and Federgruen (1993), Chandra (1993), Cohen (1993, 1994), Slats et al (1995), Federgruen and Simchi-Levi (forthcoming)). Reviews on these related works can be found in Bhatnangar et al (1993), Thomas and Griffin (1996), Vidal and Goetschalckx (1997), Baita andUkovich (1998), andErengüç et al (1999).…”

CentralizedVERSUSdecentralized production planning

“…William in [3] presents seven heuristic algorithms for scheduling production and distribution operation. He also in [4] develops a dynamic programming algorithm for simultaneously determination of the production and distribution batch sizes at each node within a supply chain network.…”