Nondominated Sorting Genetic Algorithm II for Solving an Integrated Production and Transportation Optimization Problem

• Published in: Chinese Control and Decision Conference pp. 01 - 07
• Main Authors: Wang, Wei, Qian, Bin
• Format: Conference Proceeding
• Language: English
• Published: IEEE 16.05.2025
• Subjects: Computational complexity; Genetic algorithms; Heuristic Rule; Integrated Production and Transportation; Logistics; Mathematical models; Multi-Objective Optimization; NSGA-II; Optimization; Production; Reliability; Sorting; Transportation
• ISSN: 1948-9447
• DOI: 10.1109/CCDC65474.2025.11090365

The integrated production and transportation optimization problem (IPTOP) has gained significant attention due to its critical role in in manufacturing and logistics systems. This paper focuses on a specific kind of IPTO, namely the distributed flow-shop production and loading transportation integrated optimization problem (DFPLTIP), with the objective to minimize production makespan and transportation cost. Firstly, the mathematical model of DFPLTIP is formulated in stages. Secondly, given that DFPLTIP involves the coupling of subproblems from both the production and transportation stages, a heuristic rule based on job completion time and two dimensions ((i.e., length and width) is proposed to reduce the overall computational complexity of solving DFPLTIP. This rule effectively decouples the subproblems and so speed up the identification of high-quality solutions for the DFPLTIP. Thirdly, the nondominated sorting genetic algorithm II (NSGAII), combined with the proposed heuristic rule, is employed to solve DFPLTIP. Finally, experimental results on 15 benchmark instances validate the effectiveness of the proposed approach.