Uncertain Chance-Constrained Model for Energy Consumption in the Permutation Flow Shop

Abstract This paper addresses the consumption energy in the permutation flow shop within the framework of uncertainty theory. It proposes an uncertain chance-constrained programming model. Moreover, we employ some properties of uncertainty theory to build the corresponding deterministic equivalent model which is solved by a discrete eagle strategy combined with the sine-cosine algorithm (SCA). Additionally, numerical results are reported to demonstrate the applicability of the proposed model. We have also tested the proposed algorithm with the well known PFSP benchmarks to show the performance of the proposed algorithm.