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A novel mixed-integer linear programming formulation for continuous-time inventory routing
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DOI：10.1016/j.cor.2024.106883.png)
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Inventory management, vehicle routing, and delivery scheduling decisions are simultaneously considered in the context of the inventory routing problem. This paper focuses on the continuous-time version of this problem where, unlike its more traditional discrete-time counterpart, the distributor is required to guarantee that inventory levels are maintained within the desired intervals at any moment of the planning horizon. In this work, we develop a compact mixed-integer linear programming formulation to model the continuous-time inventory routing problem. We further discuss means to expedite its solution process, including the adaptation of well-known rounded capacity inequalities to tighten the formulation in the context of a branch-and-cut algorithm. Through extensive computational studies on a suite of 90 benchmark instances from the literature, we show that our branch-and-cut algorithm outperforms the state-of-the-art approach. We also consider a new set of 63 instances adapted from a real-life dataset and show our algorithm's practical value in solving instances with up to 20 customers to guaranteed optimality.
Keyword:
Continuous-time inventory routing
Inventory management
Vehicle routing
Branch-and-cut
Rounded capacity inequalities
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4.3
论文数:
6.5K
被引数:
1.8W
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