Minimizing the Lateness, Makespan, And Energy Efficient Factors in Job Shop Scheduling

Abstract

Half of the worldwide energy is consumed by industries. In the modern era, due to an increase in the energy overhead, it is necessary to plan during electricity production. In this paper, a novel mathematical model is proposed which determine a more efficient scheduling algorithm that reduces the electricity consumption cost (ECC) and make-span for the Flexible Job Shop Scheduling Problem (FJSSP) with a time-of-use (TOU) policy. Another subtask named speed selection, which indicates the selection of varying operation speed is added to already available two subtasks of FJSSP. Subsequently, a Modified Cooperative Co-evolutionary Cuckoo Search Algorithm (MCCCSA) along with Variable Neighborhood Search (VNS) is used for resolving the constrained, unconstrained optimization and engineering issues. The population used for this algorithm is an organization that contains dynamic persons. Experimental analysis is done to check the performance of the proposed model MCCCSA+VNS for improved scheduling result when evaluated with other existing methods.