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Abstract
This study presents different approaches to deal with milk-run issue in Lean Supply Chain (LSC) management, which was introduced by Zhou and Kelin (2011). At first, these authors built up a theoretical total cost model for LSC using milk-run logistics. Afterwards, the model was applied in a LSC case study in automobile industry and then solved by improved Ant Colony Optimization (ACO) combining with classic optimal technique. Although the obtained result was acceptable, it did not achieve an optimal value. To optimize the solution, Mixed Integer Programming (MIP) and hybrid ACO and Tabu Search (HAT) approaches are proposed to resolve this issue in general. In the small-scale LSC, MIP is qualified through data from the case study while HAT is tested with random data in large size LSC. The solutions show that MIP can attain optimal outcome and HAT outperforms ACO regarding LSC total cost.
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1.Introduction
In order to survive and develop in the fierce pressures of globalization, enterprises relentlessly seek measures to enhance the performance of their supply chain (SC). By improving SC performance, enterprises can cut down inventories, improving service levels (Panneerselvam, 2007) and gain a competitive advantage (Angerhofer & Angelides, 2006). Among several SC models that have been studied and applied, LSC is evaluated as an "ideal SC" (Srinivasan, 2012) owing to the ability of supplying final products/ services to consumers promptly, and economically in a seamless manner. Paschal et al. (2012) state that when Lean Manufacturing (LM) concepts are implemented across the entire SC, the SC is considered as LSC. Anand & Kodali (2008) summarize 59 LM tools/ techniques used to transform fat SC into LSC, in which milk-run delivery is one prevalent technique.
In SC management, Milk-run is one of the most efficient and regular transportation models (Kitamura & Okamoto, 2012). It is defined as "A route on which a truck either delivers product from a single supplier to multiple retailers or goes from multiple suppliers to a single buyer location" (Sunil & Peter, 2013). This network maximizes the capacity of vehicles by conveying items in small quantities with high frequency among all members instead of large stuff from individual company. To balance with milk-run pace, companies keep production at the level that...