A heuristic approach to n/m job shop scheduling: Fuzzy dynamic scheduling algorithms

n/m shop scheduling is a 'NP-Hard' problem. Using conventional heuristic algorithms (priority rules) only, it is almost impossible to achieve an optimal solution. Research has been carried out to improve the heuristic algorithms to give a near-optimal solution. This paper advocates a fuzzy logic based, dynamic scheduling algorithm aimed at achieving this goal. The concept of new membership functions is discussed in the algorithm as a link to connect several priority rules. The constraints to determine the membership function of jobs for a particular priority rule are established, and three membership functions are developed. In order to decide the weight vector of priority rules, an aggregate performance measure is suggested. The methodology for constructing the weight vector is discussed in detail. Experiments have been carried out using a simulation technique to validate the proposed scheduling algorithm.