An Empirical Comparison of Tabu Search, Simulated Annealing, and Genetic Algorithms for Facilities Locations Problems.
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH
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Operations managers are typically faced with the need to find good solutions to difficult problems. Such problems include job scheduling, assembly line balancing, process layout, project scheduling, and facilities locations. Although optimal solutions are preferable, the combinatorial nature of these problems means that in many cases problems found in practical applications cannot be solved to optimality within reasonable resources. In these cases, operations managers turns to heuristics. Since the early 1980s, much interest has been devoted to the development and application of three general heuristic algorithms tabu search, simulated annealing, and genetic algorithms. Each of them specifies a strategy for searching the solution space of a problem looking for good local optima. From a practical point of view, we would like to know if any of these methods is indeed better than the other two. In this research study we conduct an empirical comparison of these three heuristic algorithms using three variants of the facilities location problem capacitated CFLP, multiple-periods MP-FLP, and multiple-commodities MC-FLP. The selection of three different problem structures allowed us to explore the behavior of the heuristics under different circumstances and constraints. Furthermore, none of the heuristics have been previously applied to these problems.
- Numerical Mathematics
- Operations Research