An effective genetic algorithm for just-in-time production planning in job manufacturing systems

A simple and universal gene encoding scheme for just-in-time production planning in job manufacturing systems was presented, by which a production planning directly corresponds to an ordering string. For the encoding, three important genetic operators; selection, crossover and mutation were contrived and descibed in detail. In order to increase the algorithm's capacity of global convergence, some strategies such as adaptive probability of mutation, calculating the degree of similarity, niche technology based on preselection, multigroup parallel and combining with heuristic approach were adopted.