Desert sparrow optimization algorithm for the bicriteria flow shop scheduling problem with sequence-independent setup time

Bicriteria flow shop scheduling problem with sequence-independent setup time is addressed in this paper. The objective of the scheduling problem is to minimize the system utilization time relative to the minimum value of makespan. To handle both sequence-independent setup time and job processing time independently, a mixed-integer programming model has been formulated. Since the flow shop scheduling problems with sequence-independent setup time are typically NP-complete in nature, a modified heuristic based on nature-inspired Desert Sparrow Optimization (DSO) algorithm with novel initial feasible solution technique, backward to forward shift mechanism, and tie-breaking strategy, is developed and implemented in the present work to solve the aforementioned scheduling problem. Further, to optimize both the referred objectives of scheduling, the delay time for the available system of machines is formulated. A computational experiment is carried out to evaluate the performance of the proposed heuristic for up to 500 jobs and 20 machines. The comparative analysis with the help of a defined response variable average relative percentage deviation (ARPD) verifies that the proposed technique is an effective approach when compared with other constructive heuristics for referred scheduling problem of the flow shop environment.