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B2B multi-attribute e-procurement: an artificial immune system based goal programming approach

机译:B2B多属性电子采购:基于人工免疫系统的目标编程方法

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摘要

This paper presents an artificial immune system (AIS) based goal programming approach for a multi-attribute e-procurement system. Current trends reveal that procurers are now concerned with various attributes of supplier selection, rather than negotiating only on cost. The scenario considered in this paper pertains to the procurement of an homogenous item in a large quantity. In these circumstances, procurers are forced to incorporate multi-attribute bids, dynamics pricing, related business requirements and multiple criteria in bid evaluation. The prime objective is to decide on the supplier and the quantity to be procured from the selected supplier. The problem considered here is NP hard, even without taking into account business constraints, and it becomes computationally prohibitive with an increase in the number of bids and the number of attribute values. In order to solve this problem with minimal computational time and effort, an evolutionary algorithm AIS with a goal programming technique is adopted. The working of the AIS based goal programming approach is evaluated by implementing it for a few simulated problem instances of changing complexity. The effectiveness of the proposed approach is established by a comparative study with other established evolutionary approaches such as a genetic algorithm and a simulated annealing algorithm.
机译:本文提出了一种基于人工免疫系统(AIS)的多属性电子采购系统目标编程方法。当前趋势表明,采购商现在关注供应商选择的各种属性,而不是仅就成本进行谈判。本文考虑的场景与大量同质物品的采购有关。在这种情况下,采购商被迫在投标评估中纳入多属性投标,动态定价,相关业务要求和多个标准。主要目标是确定供应商和要从选定供应商处采购的数量。即使不考虑业务限制,此处考虑的问题也是NP难题,并且随着投标数量和属性值数量的增加,它在计算上变得令人望而却步。为了以最小的计算时间和精力来解决该问题,采用了具有目标编程技术的进化算法AIS。通过针对一些不断变化的复杂性的模拟问题实例实施该方法,可以评估基于AIS的目标编程方法的工作情况。通过与其他已建立的进化方法(例如遗传算法和模拟退火算法)进行比较研究,确定了该方法的有效性。

著录项

  • 来源
    《International Journal of Production Research》 |2011年第4期|p.321-341|共21页
  • 作者单位

    Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Horn, Hong Kong;

    Department of Quantitative Methods and Operations Management, Indian Institute of Management, Kozhikode 673570, India;

    Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur 721302, India;

    Department of Management Studies, Indian Institute of Technology (IIT), Hauz Khas,New Delhi 110016, India;

    Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Horn, Hong Kong;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    evolutionary algorithms; e-business; dynamic pricing; multi-attribute bids;

    机译:进化算法;电子商务;动态定价;多属性出价;
  • 入库时间 2022-08-17 13:38:17

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