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<p>This paper studies a novel integrated production scheduling and vehicle routing problem with order acceptance. The problem entails selecting a subset of orders for acceptance, followed by determining a production schedule and delivery plan that adheres to the committed due dates. The objective is to maximize the revenue from accepted orders. To address this NP-hard problem, this paper proposes a mixed-integer linear programming (MILP) model and develops an enhanced adaptive general variable neighborhood search (AGVNS) algorithm incorporating a novel adaptive shaking mechanism. Experimental results demonstrate that the proposed algorithm achieves both high solution quality and computational efficiency.</p>

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An improved adaptive general variable neighborhood search algorithm for the integrated production scheduling and vehicle routing problem with order acceptance

  • 期刊论文

  • 发表日期：

    2026年6月3日

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  • Baoyu Liao,
  • Dan Luo,
  • Xing Zhu,
  • Panos M. Pardalos,
  • Xiaosong Huang

摘要

This paper studies a novel integrated production scheduling and vehicle routing problem with order acceptance. The problem entails selecting a subset of orders for acceptance, followed by determining a production schedule and delivery plan that adheres to the committed due dates. The objective is to maximize the revenue from accepted orders. To address this NP-hard problem, this paper proposes a mixed-integer linear programming (MILP) model and develops an enhanced adaptive general variable neighborhood search (AGVNS) algorithm incorporating a novel adaptive shaking mechanism. Experimental results demonstrate that the proposed algorithm achieves both high solution quality and computational efficiency.