A novel swarm optimization technique for partner selection in virtual enterprise

N. Nayak, Prasanna K., S. Datta, S. Mahapatra, S. Sahu
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引用次数: 7

Abstract

Partner selection is a critical issue in formation of virtual enterprises and increasing its operational effectiveness. Such a problem belongs to combinatorial optimization category and known as NP-hard problem. Usually, evolutionary methods are being adopted to obtain near-optimal solutions. In this paper, a variant of swarm optimization is proposed to handle combinatorial problems efficiently compared to its continuous counterpart. The method substantially reduces the number of tuning parameters in the algorithm. The algorithm presented include main crucial factors for partner selection such as the running cost, reaction time and running risk and select the partners for various processes that minimizes total cost. The working of the algorithm is demonstrated with the help of a typical example. Exhaustive simulation illustrates the effectiveness of algorithm.
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一种新的虚拟企业合作伙伴选择的群优化技术
合作伙伴选择是虚拟企业形成和提高其运营效率的关键问题。这类问题属于组合优化的范畴,被称为np困难问题。通常,采用进化方法来获得接近最优的解。本文提出了一种改进的群体优化算法来有效地处理组合问题。该方法大大减少了算法中调优参数的数量。该算法考虑了运行成本、反应时间和运行风险等影响合作伙伴选择的关键因素,并以最小的总成本为目标选择不同过程的合作伙伴。通过一个典型算例说明了该算法的有效性。穷举仿真验证了算法的有效性。
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