Generating Pareto schedules with outsource and internal parallel resources

Abstract The outsourcing of manufacturing operations continues to gain popularity, forcing companies to deal with the issue of scheduling orders in increasingly complex supply chains. This paper addresses a supply chain scheduling problem where both internal and external/outsourced parallel resources are available and the objectives are to minimize the number of late orders and the total outsource machine time. Both criteria are significant since the former is a measure of the degree of customer service while the latter represents an important cost measure. Several heuristics are developed that generate sets of Pareto-efficient schedules. The bi-criteria performance of the heuristics is assessed employing three existing methods for evaluating efficient solution sets. The evaluation (comparison of the heuristics) is based on two experiments where the values of relevant parameters (e.g., due date tightness or number of jobs) are set at different levels. These performance evaluations and comparisons between heuristics show that various approaches work well, each dominating under particular conditions of experimental variables.