Abstract
The effective distribution of relief to an emergency logistics system plays a crucial role during the disaster response phase. Considering stochastic characteristics of relief demand, this study investigates the robust optimization of a multi-objective multi-period location-routing problem for epidemic logistics, a special emergency logistics, with uncertain scenarios. A corresponding robust multi-objective multi-period optimization model is proposed, which aims to determine the optimal location of temporary relief distribution centres and route planning simultaneously. The optimization objectives include the total travel time, the total cost, and the disutility of relief service. To solve the above optimization model, a preference-inspired co-evolutionary algorithm with Tchebycheff decomposition (PICEA-g-td) is given. The performance of the proposed PICEA-g-td is evaluated by comparing it with NSGA-II, MOEA/D and PICEA-g. The experimental results show that the proposed algorithm performs better than the other three algorithms in terms of the solution quality. Finally, some useful management insights are obtained.
Highlights
Outbursts of emergencies from public health events have occurred worldwide, causing a large number of deaths
Before deducing the robust counterpart of the MMRLRP, the robust optimization method proposed by Bertsimas and Sim [21] and Najafi et al [55] is introduced as follows:
Since Eq (14) involves uncertain parameters, the MMRLRP deduces its robust counterpart using the robust optimization method proposed by Bertsimas and Sim [21]
Summary
Outbursts of emergencies from public health events have occurred worldwide, causing a large number of deaths. Locating disaster temporary relief centres and planning rational routes to provide relief to these hospitals have a significantly positive impact on the overall performance of epidemic logistics Infection materials, such as medical materials and daily supplies during the epidemic outbreak, were defined as class 6 hazardous materials by the Jefferson Lab [9]. Considering that information about the relief needs is imprecise as the epidemic disaster progresses, it is one of the most important decisions for emergency logistics management to dynamically optimize temporary relief distribution centres and route planning [16]. This study considers a multi-objective multi-period robust location-routing problem with uncertain demand (MMRLRP) to optimize epidemic logistics during public health events. The main contributions of this paper are shown as follows: First, a robust optimization model on a multi-objective location-routing problem for epidemic logistics system design with multi-period is proposed.
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