Abstract: Procurement auction plays an import role for sourcing items (products and/or services), which significantly affects the purchase performance. Literature on bundling from buyer’s perspective is quite scarce. Bundling from buyer’s perspective is the problem of determining a set of mutually exclusive bundles from the buyer perspective, which will induce competitive bidding behavior under the constraint that suppliers are required to bid on all the items in a bundle. In this paper, we present a buy-side perspective on bundling, by clarifying the definitions of the concepts of a bundle and a bundling solution, and introduce a 0-1 integer program optimization model, with the objective of minimizing the number of bundles in the bundling solution. The optimization model is proved to be NP-hard. For the sake of efficiently solving this problem, the model is first transformed into a traveling salesman problem and then solved using a genetic algorithm proposed in this paper. The performance of the proposed approach is compared with those of a traditional integer program solver and an existing bi-clustering approach. The experimental results show that the proposed approach can provide promising results in terms of a bundling solution and computing efficiency.

Key words: procurement auction, bundling from the buyer perspective, traveling salesman problem, genetic algorithm

摘要： 招标采购是采购物品(货物或服务)的有效方式, 采购物品打包是招标采购的重要环节并对采购绩效有重要影响。采购物品打包是确定一组互斥的采购包集合, 在充分的市场竞争条件下购买全部采购物品, 且每个采购包的候选供应商应对该采购包中的所有物品进行投标。目前采购物品打包问题的研究文献较少, 本文通过定义采购包和采购打包方案等概念, 建立了采购物品打包问题的0-1整数规划模型。由于该模型具有NP-hard特征, 为此首先将其转化为旅行商问题, 并基于遗传算法设计采购物品打包问题的求解算法。实验表明:与整数规划求解软件和双聚类算法相比, 本文所提出的算法在解决采购物品打包问题时具备更好的优化性能和计算效率。

关键词: 招标采购, 采购物品打包, 旅行商问题, 遗传算法