Showing papers by "Chris N. Potts published in 1996"
TL;DR: A detailed functional simulation model, which generates a multifunction radar environment, has been developed to aid the evaluation of the various scheduling heuristics that are proposed.
95 citations
TL;DR: An On log n time heuristic that is based on Johnson's algorithm is presented and it is shown to generate a schedule with length at most 5/3 times that of an optimal schedule, thereby reducing the previous best available worst-case performance ratio.
Abstract: This paper considers the problem of sequencing n jobs in a three-machine flow shop with the objective of minimizing the makespan, which is the completion time of the last job. An On log n time heuristic that is based on Johnson's algorithm is presented. It is shown to generate a schedule with length at most 5/3 times that of an optimal schedule, thereby reducing the previous best available worst-case performance ratio of 2. An application to the general flow shop is also discussed.
58 citations
TL;DR: Four alternative local search methods are proposed: multi-start descent, simulated annealing, tabu search and a genetic algorithm; the best results are obtained with the genetic algorithm.
38 citations
TL;DR: Based on the results of extensive computational tests, simulated annealing is found to generate better quality solutions than the other neighborhood search methods, but results also indicate that the hybrid genetic descent algorithm is superior to simulatedAnnealing.
Abstract: Local search techniques are widely used to obtain approximate solutions to a variety of combinatorial optimization problems. Two important categories of local search methods are neighbourhood search and genetic algorithms. Commonly used neighbourhood search methods include descent, threshold accepting, simulated annealing and tabu search. In this paper, we present a computational study that compares these four neighbourhood search methods, a genetic algorithm, and a hybrid method in which descent is incorporated into the genetic algorithm. The performance of these six local search methods is evaluated on the problem of scheduling jobs in a permutation flow shop to minimize the total weighted completion time. Based on the results of extensive computational tests, simulated annealing is found to generate better quality solutions than the other neighborhood search methods. However, the results also indicate that the hybrid genetic descent algorithm is superior to simulated annealing.
37 citations
2 citations