کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
385974 | 660876 | 2011 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A multi-criteria customer allocation problem in supply chain environment: An artificial immune system with fuzzy logic controller based approach A multi-criteria customer allocation problem in supply chain environment: An artificial immune system with fuzzy logic controller based approach](/preview/png/385974.png)
In the present day business environment, customer satisfaction is a pre-requisite for providing good service to the customer. The present day market is a customer driven market and only those who can fulfill customer demands at minimal rate and in shortest time can share a greater market share. Owing to the aforementioned factors, the problem of customers’ allocation to the vendors is considered to be very important problem and has attracted the attention of a lot of researchers. In this paper, a multiple vendor transportation problem having a variety of products and multiple customers has been taken into consideration. The problem considers two criteria: transportation time and transportation cost, thus making it a multi-criteria problem. To solve this problem, a heuristic based on a new approach, called artificial immune system (AIS) has been proposed. To strengthen AIS, a fuzzy logic controller (FLC) has been incorporated in the AIS heuristic. FLC changes the hyper mutation rate adaptively at iteration. A benchmark problem from the prominent literature review has been taken for showing the efficacy of the proposed algorithm. The supremacy of the problem has been shown by the randomly generated data set with increased complicacy of the problems.
Research highlights
► A novel heuristic is proposed by combining the ideas from artificial immune system and fuzzy logic.
► To facilitate the decision maker to evaluate the different alterna tive solutions at the same time, some random weights are assigned.
► Proposed heuristic outperforms over the other heuristics like AIS and GA.
Journal: Expert Systems with Applications - Volume 38, Issue 4, April 2011, Pages 3199–3208