Dual-objective Job Shop Scheduling Problem with Skilled Workers

Abstract

The Job Shop Scheduling Problem (JSSP) is work allocation on workstations to produce items that have a goal to optimize a few objectives. This research aims to develop the JSSP's model that deals with machines and job sequences by dual objective functions under the new gainful constraints involving types of skilled workers according to the case study of a steel mill. The proposed methodology of this research is applied with the Memetic algorithm (Genetic algorithm and Local Search technique) and the Pareto optimization. The result generated from the proposed idea can help the manager to decide on the assignment of the right worker to operate the right machine with the right job to achieve the objective values of minimum makespan and maximum average utilization of workers.