Meta-heuristic scheduling auction applying multi-objective genetic algorithm

The Scheduling Auction (SA) integrates a VCG auction with scheduling and involves solving multiple combinatorial optimization problems. As applying a meta-heuristic to address these problems compromises some favorable properties of the VCG mechanism, mitigating this side effect is an important issue. The optimization problems have identical objective functions and share most constraint equations, differing only in some constraints for designating values of specific decision variables. By taking advantage of this feature, this study proposes the Scheduling Auction with Multi Objective Single Population Genetic Algorithm, a type of Meta-Heuristic Scheduling Auction mechanism. Computational experiments were conducted on a fictitious factory with a flow shop structure operating a Made-to-Order service to compare the social surplus, customers’ utility, and the company’s revenue.