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A Lagrangian heuristic for bid evaluation in e-procurement auctions

机译:一场拉格朗日启发式,用于电子采购拍卖中的评估

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e-Procurement is an Internet based business process for sourcing direct or indirect materials. This paper considers a procurement scenario of a buyer procuring large quantities of a single good. The suppliers submit nonconvex piecewise linear supply curves as their bids. Such bids enable the suppliers to effectively express their economies of scale and transportation constraints. The buyer imposes a business rule of limiting the winning suppliers within a preferred range. The bid evaluation problem faced by the buyer is to select the winning suppliers and their trading quantities, such that the cost of procurement is minimized while satisfying the supply, demand, and business constraints. The bid evaluation problem is NP-hard even for a simple special case. In this paper, the problem is formulated as a mixed integer linear programming problem and we propose a Lagrangian relaxation based heuristic to find a near optimal solution. The computational experiments performed on representative data sets show that the proposed heuristic produces a feasible solution with negligible optimality gap.
机译:电子采购是基于互联网的互联网业务流程,用于采购直接或间接材料。本文考虑了买方的采购方案,采购大量单一的良好。供应商提交非透明线性电源曲线作为其出价。这种出价使供应商能够有效地表达其规模和运输限制的经济。买方在首选范围内限制了胜利供应商的业务规则。买方面临的投标评估问题是选择获胜供应商及其交易量,使得采购成本在满足供应,需求和业务限制的同时最小化。甚至对于一个简单的特殊情况,BID评估问题也是NP - 硬。在本文中,该问题被制定为混合整数线性规划问题,我们提出了一种基于拉格朗日放松的启发式,可以找到近最佳解决方案。对代表性数据集进行的计算实验表明,所提出的启发式产生可行的溶液,其最优性差距可忽略不计。

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