A Comparative Representation Approach To Modern Heuristic Search Methods In A Job Shop

摘要

The job shop problem is among the class of non-deterministic polynomial time hard combinatorial problems. This research article addresses the problem of static job shop scheduling on the job-based representation and the rule-based representations. The popular search techniques, such as the genetic algorithm and simulated annealing are used for the determination of the objectives like minimisations of the makespan time and mean flow time. Various rules, such as the SPT, LPT, MWKR and LWKR are used for the objective function to attain the results. The summary of results from this article gives a conclusion that the genetic algorithm gives better results in the makespan time determination on both the job-based representation and the rule-based representation and the simulated annealing algorithm gives the better results in the mean flow time in both the representations.