Fuzzy Multi-Objective Parallel Machines Scheduling Problem through New Solution Method

One of the basic and significant problems that a shop or a factory manager encounters is a suitable scheduling and sequencing of jobs on machines. One type of scheduling problem is just-in-time scheduling. Motivated by just-intime manufacturing, we consider the multi-objective problem. These objectives minimize total weighted tardiness, earliness and minimize total flow time with fuzzy parameters on parallel machines, simultaneously with respect to the impact of machine deterioration. A number of different methods such as branch and bound, cutting plane, and other heuristic methods can solve the above problem. In recent years, researches have used genetic algorithms, simulated annealing, and machine learning methods for solving such problems. This problem is known as NP-hard. We discuss several dominance properties of optimal solutions, then present mathematical model and propose one method for defuzzification.