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An integrated model for the optimisation of a two-echelon supply network

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Języki publikacji
EN
Abstrakty
EN
Purpose: The purpose of this paper is to develop a mixed integer formulation that extends the previous production-distribution models by the integration of Aggregate Production Plan and Distribution Plan. Design/methodology/approach: This paper, firstly, presents a comprehensive review and analysis on the proposed production-distribution models and would develop a summary table to describe the main characteristics of the selected models outlining the level of complexity considered at each study. Based on the integration of Aggregate Production Plan and Transportation/Distribution Plan, over the second stage, the paper will develop a mixed integer formulation for a two-echelon supply network. The model incorporates multi-time periods, multi-products, multi-plants, multi-warehouses as well as multi-end users, and considers the real-world variables and constraints. Finally, the developed model will be analyzed in case of a realistic scenario-based production-distribution problem. Findings: This paper developed a mixed integer formulation for the optimization of a two-echelon SN. Considering detailed production cost elements and a realistic range of variables and constraints in the proposed case study indicate the effectiveness of the developed model in the real-world applications. Practical implications: The increasing interest in evaluating the performance of SNs over the last years indicates the need for the development of complex optimization models able to answer unsolved questions in the production-distribution network. Originality/value: Implementation of a supply-chain (SC) system has crucial impacts on a company's financial performance. Overall performance of a Supply Network (SN) is influenced significantly by the decisions taken in its production-distribution plan integrating the decisions in production, transport and warehousing as well as inventory management. Thus, one key issue in the performance evaluation of SNs is the modeling and optimization of production-distribution plan considering its actual complexity.
Rocznik
Strony
477--484
Opis fizyczny
Bibliogr. 20 poz., wykr.
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autor
autor
Bibliografia
  • [1] M. A. Cohen, H. L. Lee, Strategic analysis of integrated production-distribution systems: models and methods Operations Research Society of America 36/2 (1988) 216-228.
  • [2] P. Chandra, M. L. Fisher, Coordination of production and distribution planning, European Journal of Operational Research 72/3 (1994) 503-517.
  • [3] D. F. Pyke M. A. Cohen, Multiproduct integrated productiondistribution systems, European Journal of Operational Research 74/1 (1994) 18-49.
  • [4] A. Alfieri, P. Brandimarte, Object-oriented modeling and simulation of integrated production/distribution systems, Computer Integrated Manufacturing Systems 10/4 (1997) 261-266.
  • [5] G. Barbarosoglu, D. Ozgur Hierarchical design of an integrated production and 2-echelon distribution system, European Journal of Operational Research 118/3 (1999) 464-484.
  • [6] L. Young Hae, K. Sook Han, Optimal production-distribution planning in supply chain management using a hybrid simulation-analytic approach, Proceedings of the Winter Simulation Conference, Orlando, 2000.
  • [7] V. Jayaraman, H. Pirkul, Planning and coordination of production and distribution facilities for multiple commodities, European Journal of Operational Research 133/2 (2001) 394-408.
  • [8] A. Syarif, Y. Yun, et al., Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach, Computers and Industrial Engineering 43/1-2 (2002) 299-314.
  • [9] S. S. Syam, A model and methodologies for the location problem with logistical components, Computers and Operations Research 29/9 (2002) 1173-1193.
  • [10] K. S. Bhutta, F. Huq, et al., An integrated location, production, distribution and investment model for a multinational corporation, International Journal of Production Economics 86/3 (2003) 201-216.
  • [11] F. T. S. Chan, S. H. Chung, et al., A hybrid genetic algorithm for production and distribution, Omega 33/4 (2005) 345-355.
  • [12] M. Gen, A. Syarif' ”Hybrid genetic algorithm for multi-time period production/distribution plannin”, Computers and Industrial Engineering 48/4 (2005) 799-809.
  • [13] W.-C. Yeh, A hybrid heuristic algorithm for the multistage supply chain network problem, The International Journal of Advanced Manufacturing Technology 26 (2005) 675-685.
  • [14] W.-C. Yeh, An efficient memetic algorithm for the multi-stage supply chain network problem, The International Journal of Advanced Manufacturing Technology 29/7 (2006) 803-813.
  • [15] S. J. Lim, S. J. Jeong, et al., A simulation approach for production-distribution planning with consideration given to replenishment policies, International Journal of Advanced Manufacturing Technology 27/5 (2006) 593-603.
  • [16] T. Nishi, M. Konishi, et al., A distributed decision making system for integrated optimization of production scheduling and distribution for aluminum production line, Computers and Chemical Engineering 31/10 (2007) 1205-1221.
  • [17] R. A. Aliev, B. Fazlollahi, et al., Fuzzy-genetic approach to aggregate production-distribution planning in supply chain management, Information Sciences 177/20 (2007) 4241-4255.
  • [18] F. Altiparmak, M. Gen, et al., A genetic algorithm approach for multi-objective optimization of supply chain networks, Computers and Industrial Engineering 51/1 (2006) 196-215.
  • [19] Altiparmak, F. M. Gen, et al., A steady-state genetic algorithm for multi-product supply chain network design, Computers and Industrial Engineering (2007) In Press, Corrected Proof.
  • [20] R. Z. Farahani, M. Elahipanah, A genetic algorithm to optimize the total cost and service level for just-in-time distribution in a supply chain, International Journal of Production Economics 111/2 (2008) 229-243.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWAW-0002-0045
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