Optimal production scheduling with multi-round information interaction for demander-dominated decentralized scheduling problem

Demander-dominated market scenarios are becoming increasingly common owing to the emergence of alternative service providers and competitive market environment. However, these scenarios have not been considered in previous studies pertaining to decentralized scheduling problems. Thus, service providers cannot formulate optimal production scheduling schemes for such scenarios. In this study, we investigate a demander -dominated decentralized scheduling problem in which the demander can adopt the private-strategic behavior of transferring partial orders towards its alternative service providers. The aim of this study is to provide guidance to service providers for developing high-quality production scheduling solutions under asymmetric information. First, we design a multi-round information interaction mechanism with a learning strategy to realize information interaction. Subsequently, a metaheuristic algorithm termed MAM is developed based on the multi-round information interaction mechanism to solve the proposed problem. A problem-dependent initialization method and a solution generation method integrating the learning strategy are developed to improve the search efficiency. Experimental results indicate the usefulness of the initialization method and learning strategy. Based on a comparison with two well-established adapted algorithms, the effectiveness of the proposed algorithm is confirmed, particularly for instances with loose due dates. Furthermore, we analyze the effect of MAM on both the service provider and the demander by comparing it with traditional centralized approaches. Statistical results show that the proposed algorithm yields high-quality solutions for the service provider and that maintaining the confidentiality of private information is conducive to the demander, particularly when the due dates are tight.

Automated summary

This study investigates a demander-dominated decentralized scheduling problem where the demander can adopt private-strategic behavior. A multi-round information interaction mechanism with a learning strategy is designed to solve the problem, and the proposed algorithm is shown to yield high-quality solutions for service providers. Additionally, the confidentiality of private information is found to be beneficial for the demander, particularly in cases with tight due dates.