A N–N optimization model for logistic resources allocation with multiple logistic tasks under demand uncertainty
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It is challenging to make an optimal allocation scheme for multiple paralleling logistics tasks match suitable resources in collaborative logistics network (CLN) due to the uncertainty. In this paper, we propose a multi-objective optimization mathematical model to solve the N–N task-resource assignment (TRA) problem in CLN under demand uncertainty. Chance constraint in the model is used to indicate demand uncertainty, and resource leveling is considered in the execution of multiple paralleling logistics tasks scheduling. A hybrid heuristic algorithm based on genetic algorithm and tabu search is presented to solve the N–N TRA model. The experimental results demonstrate that the proposed model can promisingly describe the TRA problem, and the hybrid heuristic algorithm can achieve superior result about the size of uncertainty degree on allocation scheme.
KeywordsTask-resource assignment Demand uncertainty Task scheduling Resource leveling
This work was supported by National Natural Science Foundation of China (Grant No. 71771208), the Fundamental Research Funds for the Central Universities, China (Grant No. 17CX04023B), and partly supported by the Welsh Government and Higher Education Funding Council for Wales through the Sêr Cymru National Research Network for Low Carbon, Energy and Environment (NRN-LCEE).
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Conflict of interest
The authors declare that they have no conflict of interest.
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