EURO 2025 Leeds
Abstract Submission

1358. Distributionally robust inventory routing for recycling waste batteries under uncertain quality

Invited abstract in session WB-15: Discrete, continuous or stochastic optimization and control in networks, transportation and design 2, stream Combinatorial Optimization.

Wednesday, 10:30-12:00
Room: Esther Simpson 1.08

Authors (first author is the speaker)

1. Xinyi Zhang
2. Ada Che
School of Management, Northwestern Polytechnical University

Abstract

This paper addresses, for the first time, an uncertain inventory routing problem for waste battery recycling, managed by multiple regional collection centers (RCCs) with uncertain waste battery qualities. Given a planning horizon and cascade utilization demands, the problem aims to find the optimal number of waste batteries to be collected from RCCs and the transportation routes to minimize the total cost, including recycling, processing, and the risk measure costs over all uncertain battery qualities defined by an ambiguity set. We first formulate the problem into a two-stage distributionally robust optimization model, where one sub-model is non-linear due to the uncertain waste battery quality and the impact of worst-case scenarios on inventory and shortages. A linearized equivalent reformulation is then derived based on exploring the nonlinear nature of the sub-model's objective function and using McCormick inequalities. Then, a decomposition-based exact algorithm is developed based on this reformulation. To enhance its performance, we implement it within a branch-and-check framework and introduce two families of symmetry-breaking inequalities. Finally, we conduct extensive numerical experiments to validate the effectiveness of the proposed method in both static and dynamic settings, deriving insights into how the presence of uncertain waste battery quality and the sufficiency of recycling information influence corporate costs and decision-making.

Keywords

Status: accepted

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