Marc Goetschalckx

A stochastic programming approach for supply chain network design under uncertainty

This paper proposes a stochastic programming model and solution algorithm for solving supply chain network design problems of a realistic scale. Existing approaches for these problems are either restricted to deterministic environments or can only address a modest number of scenarios for the uncertain problem parameters. Our solution methodology integrates a recently proposed sampling strategy, the sample average approximation (SAA) scheme, with an accelerated Benders decomposition algorithm to quickly compute high quality solutions to large-scale stochastic supply chain design problems with a huge (potentially infinite) number of scenarios. A computational study involving two real supply chain networks are presented to highlight the significance of the stochastic model as well as the efficiency of the proposed solution strategy.

Strategic production-distribution models: A critical review with emphasis on global supply chain models

Abstract An extensive literature review of strategic production-distribution models is presented in this article. The review is classified into four sections: Previous reviews, Optimization models, Additional issues for modeling, and Case studies and applications. The review of mixed integer programming models is a fundamental part of this paper. It focuses on the identification of the relevant factors included in the formulations, and the specific characteristics of solution methods and computational experiences. Summary tables, describing the main characteristics of selected models found in the literature, are also presented. Special emphasis is placed on models for global logistics systems, addressing their lack of features, and identifying opportunities for further research in this area.

Research on warehouse operation: A comprehensive review

An extensive review on warehouse operation planning problems is presented. The problems are classified according to the basic warehouse functions, i.e., receiving, storage, order picking, and shipping. The literature in each category is summarized with an emphasis on the characteristics of various decision support models and solution algorithms. The purpose is to provide a bridge between academic researchers and warehouse practitioners, explaining what planning models and methods are currently available for warehouse operations, and what are the future research opportunities.

Modeling and design of global logistics systems: A review of integrated strategic and tactical models and design algorithms

The overall focus of this research is to demonstrate the savings potential generated by the integration of the design of strategic global supply chain networks with the determination of tactical production–distribution allocations and transfer prices.The logistics systems design problem is defined as follows: given a set of potential suppliers, potential manufacturing facilities, and distribution centers with multiple possible configurations, and customers with deterministic demands, determine the configuration of the production–distribution system and the transfer prices between various subsidiaries of the corporation such that seasonal customer demands and service requirements are met and the after tax profit of the corporation is maximized.The after tax profit is the difference between the sales revenue minus the total system cost and taxes.The total cost is defined as the sum of supply, production, transportation, inventory, and facility costs.Two models and their associated solution algorithms will be introduced.The savings opportunities created by designing the system with a methodology that integrates strategic and tactical decisions rather than in a hierarchical fashion are demonstrated with two case studies. The first model focuses on the setting of transfer prices in a global supply chain with the objective of maximizing the after tax profit of an international corporation.The constraints mandated by the national taxing authorities create a bilinear programming formulation.We will describe a very efficient heuristic iterative solution algorithm, which alternates between the optimization of the transfer prices and the material flows.Performance and bounds for the heuristic algorithms will be discussed. The second model focuses on the production and distribution allocation in a single country system, when the customers have seasonal demands.This model also needs to be solved as a subproblem in the heuristic solution of the global transfer price model.The research develops an integrated design methodology based on primal decomposition methods for the mixed integer programming formulation.The primal decomposition allows a natural split of the production and transportation decisions and the research identifies the necessary information flows between the subsystems.The primal decomposition method also allows a very efficient solution algorithm for this general class of large mixed integer programming models.Data requirements and solution times will be discussed for a real life case study in the packaging industry. � 2002 Elsevier Science B.V. All rights reserved.

Research on warehouse design and performance evaluation: A comprehensive review

This paper presents a detailed survey of the research on warehouse design, performance evaluation, practical case studies, and computational support tools. This and an earlier survey on warehouse operation provide a comprehensive review of existing academic research results in the framework of a systematic classification. Each research area within this framework is discussed, including the identification of the limits of previous research and of potential future research directions.

A global supply chain model with transfer pricing and transportation cost allocation

Abstract We present a model for the optimization of a global supply that maximizes the after tax profits of a multinational corporation and that includes transfer prices and the allocation of transportation costs as explicit decision variables. The resulting mathematical formulation is a non-convex optimization problem with a linear objective function, a set of linear constraints, and a set of bilinear constraints. We develop a heuristic solution algorithm that applies successive linear programming based on the reformulation and the relaxation of the original problem. Our computational experiments investigate the impact of using different starting points. The algorithm produces feasible solutions with very small gaps between the solutions and their upper bound (UB).

The vehicle routing problem with backhauls

Abstract The Vehicle Routing Problem with Backhauls is a pickup/delivery problem where on each route all deliveries must be made before any pickups. A two-phased solution methodology is proposed. In the first phase, a high quality initial feasible solution is generated based on spacefilling curves. In the second phase, this solution is improved based on optimization of the subproblems identified in a mathematical model of the problem. An extensive computational analysis of several initial solution algorithms is presented, which identifies the tradeoffs between solution quality and computational requirements. The class of greedy algorithms is capacity oriented, while K-median algorithms focus on distance. It is concluded that the greedy and K-median algorithms generate equivalent tour lengths, but that the greedy procedure reduces the required number of trucks and increases the truck utilization. The effect of exchange improvement procedures as well as optimal procedures on solution quality and run time is demonstrated. Comparisons with the Clark—Wright method adapted to backhauls are also given.

A primal decomposition method for the integrated design of multi-period production–distribution systems

We study the integrated design of strategic supply chain networks and the determination of tactical production–distribution allocations in the case of customer demands with seasonal variations. Given a set of potential suppliers, potential manufacturing facilities and distribution centers with multiple possible configurations, and customers with seasonal demands, the goal is to determine the configuration of the production–distribution system with the lowest sum of supply, production, transportation, inventory, and facility costs such that seasonal customer demands are met. We develop a mixed integer programming formulation and an integrated design methodology based on primal (Benders) decomposition. For a case study in the packaging industry, specialized acceleration techniques reduced the running times by a factor of 480. The company projects savings of 2% or

An interactive layout heuristic based on hexagonal adjacency graphs

8.3 million by using the integrated rather than the optimal hierarchical configuration.

Optimising part feeding in the automotive assembly industry: deciding between kitting and line stocking

Abstract An efficient and interactive two-stage heuristic for the generation of block layouts is presented. During the first phase, it generates a hexagonal and maximum weight planar adjacency subgraph, which incorporates relationships with the outside of the layout in a consistent manner. The user can select a variety of (graph) construction algorithms based upon unary, binary, and ternary relationships tuples. The adjacency graph can be further improved by interior and exterior exchange procedures and a tight upper bound is derived based on an integer programming formulation. During the second phase, the adjacency graph is converted into a rectangular block layout, which yields all rectangularly shaped departments. Again the user can select various heuristic (block layout) construction and improvement procedures. The combined stages avoid some of the major disadvantages of graph-theoretic and area-based facility layout procedures. The results of the graph and block layout algorithms are compared with other algorithms for selected cases in the literature. In addition, the program was designed to allow for easy, interactive algorithm selection, sensitivity analysis, and manual construction by using an industry standard graphical user interface. Algorithms were purposely kept simple to decrease response time. Graphs, block layouts, and reports are immediately displayed, and can be readily printed or exported to other programs for computer-aided detailed layout design.