A multi-objective optimization model of truck scheduling problem using cross-dock in supply chain management: NSGA-II and NRGA
Abstract
Purpose
This paper aims to develop a multi-objective problem for scheduling the operations of trucks entering and exiting cross-docks where the number of unloaded or loaded products by trucks is fuzzy logistic. The first objective function minimizes the maximum time to receive the products. The second objective function minimizes the emission cost of trucks. Finally, the third objective function minimizes the number of trucks assigned to the entrance and exit doors.
Design/methodology/approach
Two steps are implemented to validate and modify the proposed model. In the first step, two random numerical examples in small dimensions were solved by GAMS software with min-max objective function as well as genetic algorithms (GA) and particle swarm optimization. In the second step, due to the increasing dimensions of the problem and computational complexity, the problem in question is part of the NP-Hard problem, and therefore multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment.
Findings
Therefore, non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA) are used to solve 30 random problems in high dimensions. Then, the algorithms were ranked using the TOPSIS method for each problem according to the results obtained from the evaluation criteria. The analysis of the results confirms the applicability of the proposed model and solution methods.
Originality/value
This paper proposes mathematical model of truck scheduling for a real problem, including cross-docks that play an essential role in supply chains, as they could reduce order delivery time, inventory holding costs and shipping costs. To solve the proposed multi-objective mathematical model, as the problem is NP-hard, multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment. Therefore, NSGA-II and NRGA are used to solve 30 random problems in high dimensions.
Keywords
Acknowledgements
Funding: The authors did not receive support from any organization for the submitted work.
Disclosure statement: No potential competing interest was reported by the authors.
Data availability statement: The data that support the findings of this study are available from the corresponding author, upon reasonable request.
Citation
Haghgoei, A., Irajpour, A. and Hamidi, N. (2024), "A multi-objective optimization model of truck scheduling problem using cross-dock in supply chain management: NSGA-II and NRGA", Journal of Modelling in Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JM2-06-2023-0130
Publisher
:Emerald Publishing Limited
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