Scheduling Optimization in the Mass Customization of Global Producer Services

Abstract

Scheduling in the mass customization (MC) of global producer services is a typical multiobjective dynamic optimization issue, which is constrained by stochastic demand and resources. Such scheduling frequently challenges the cross-border decision-making processes of multinational enterprises (MNEs). The academic literature has yet to examine this optimization, although studies on the MC of tangible product provision are numerous. To address this challenge effectively, we construct a novel stochastic multiobjective dynamic scheduling model by considering the key features of the MC of global producer services, namely, stochastic demand, distinctive characteristics of customization orders, special stage classification, economies of scale, stochastic service capabilities, and pressures for global integration versus local responsiveness. We improve the ant algorithm to solve the scheduling problem and illustrate the feasibility, validity, and applicability of the new model and algorithm using the case of an MNE that provides seismic acquisition services for oil companies. The results suggest that the proposed algorithm can achieve the flexibility and balance of multiobjective optimization. The major optimization indicators suggest that the scheduling improved the overall economies of scale on the supply chain, which is a key factor in ensuring the success of the MC of global producer services. By incorporating the methodology of operational research and the perspective of international business, this study contributes to the literature of operational research by developing a novel scheduling model for the MC of global producer services.