Solving a multi-agent scheduling problem in a flow shop environment considering rejection and deteriorating jobs: using a meta-heuristic algorithm

A multi-agent scheduling problem in a flow shop environment has been considered in this study. Multi-agent scheduling problem is a subset of multi-objective scheduling problems in which each agent has a set of jobs and its aim is to optimize its own objective function. To make the proposed problem more realistic, two practical assumptions such as deteriorating jobs and rejection has been considered. A mixed integer programming model is presented for the problem. The main contribution of the proposed model is to consider multi-agent with two mentioned assumptions. Also, due to the complexity of the model and its inability to solve large-scale problems, a meta-heuristic Non-Dominated sorting Genetic Algorithm (NSGA-II) are developed. Obtained solutions of this algorithm are compared with exact augmented ε-constraint method and the results confirm its performance.