This paper presents an effective genetic algorithm (GA) for job shop sequencing and scheduling. A simple and universal gene encoding scheme for both single machine and multiple machine models and their corresponding genetic operators, selection, sequence-extracting crossover and neighbour-swap mutation are described in detail. A simple heuristic rule is adapted and embedded into the GA to avoid the production of unfeasible solutions. The results of computing experiments for a number of scheduling problems have demonstrated that the GA described in the paper is effective and efficient in terms of the quality of solution and the computing cost.
|Number of pages||8|
|Journal||Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture|
|Publication status||Published - 1 Apr 2000|