caa a22 4500 606159347 CHVBK 20210128100624.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s00521-015-1828-9 doi (NATIONALLICENCE)springer-10.1007/s00521-015-1828-9 A novel chaotic imperialist competitive algorithm for production and air transportation scheduling problems [Elektronische Daten] [A. Mortazavi, A. Khamseh, B. Naderi] Although production and transportation scheduling problems are of two essential issues in supply chain management, they are rarely integrated. In this paper, we study the problem of production and transportation scheduling to minimize total cost of supply chain. The problem is mathematically modeled. Moreover, a novel metaheuristic based on an imperialist competitive algorithm is developed for solving the problem. The proposed algorithm is enriched by a chaotic map and two new operators to avoid from local optima. To tune the parameters, Taguchi experimental design is applied. For evaluation of the proposed algorithm, it is compared with an available genetic algorithm. Finally, using numerical experiments, the outperformance of the proposed algorithm is shown in both solution quality and performance robustness. The Natural Computing Applications Forum, 2015 Supply chain coordination nationallicence Air transportation nationallicence Imperialist competitive algorithm nationallicence Chaos theory nationallicence Taguchi experimental design nationallicence Mortazavi A. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran aut Khamseh A. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran aut Naderi B. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran aut Neural Computing and Applications Springer London 26/7(2015-10-01), 1709-1723 0941-0643 26:7<1709 2015 26 521 https://doi.org/10.1007/s00521-015-1828-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-015-1828-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Mortazavi A. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran aut NATIONALLICENCE 700 1- Khamseh A. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran aut NATIONALLICENCE 700 1- Naderi B. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/7(2015-10-01), 1709-1723 0941-0643 26:7<1709 2015 26 521