Metaheuristic Algorithms for Supply Chain Management Problems

Metaheuristic Algorithms for Supply Chain Management Problems

Ata Allah Taleizadeh (Iran University of Science and Technology, Iran) and Leopoldo Eduardo Cárdenas-Barrón (Tecnológico de Monterrey, México)
DOI: 10.4018/978-1-4666-2086-5.ch004
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Abstract

Recently, metaheuristic algorithms (MHAs) have gained noteworthy attention for their abilities to solve difficult optimization problems in engineering, business, economics, finance, and other fields. This chapter introduces some applications of MHAs in supply chain management (SCM) problems. For example, consider a multi-product multi-constraint SCM problem in which demands for each product are not deterministic, the lead-time varies linearly with regard to the lot-size and partial backordering of shortages are assumed. Thus, since the main goal is to determine the re-order point, the order quantity and number of shipments under the total cost of the whole chain is minimized. In this chapter, the authors concentrate on MHAs such as harmony search (HS), particle swarm optimization (PSO), genetic algorithm (GA), firefly algorithm (FA), and simulated annealing (SA) for solving the following four supply chain models: single-vendor single-buyer (SBSV), multi-buyers single-vendor (MBSV), multi-buyers multi-vendors (MBMV) and multi-objective multi-buyers multi-vendors (MOMBMV). These models typically are in any supply chain. For illustrative purposes, a numerical example is solved in each model.
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Background On Supply Chain

Supply chain management (SCM) has been an important research topic in the field of operations research over last two decades, and it has established into a notion that covers strategic, tactical and operational management issues.

In recent years, the companies realize a more effective and efficient management of inventories across the whole supply chain through a better coordination and more cooperation. In this direction, they are in the joint benefit of all members involved. For this reason, the joint single-buyer single-vendor (SBSV), which the simplest form of SCM problem, has received an extensive attention in the literature. Perhaps, Goyal (1977) was the first researcher in introducing the basic single-buyer single-vendor integrated inventory model. Later, Banerjee (1986) considers that the vendor plays the role of a manufacturer with a finite production rate and uses lot-sizing policy to satisfy buyer’s requests as separate batches. Hill (1999) develops a SBSV with an unequal shipment policy and concludes that using shipment sizes which can be increased by a fixed factor in the beginning and then remaining constant after a well-specified number of shipments is an optimal policy for SBSV problem. Hariga and Ben-Daya (1999) develop a SBSV in which reorder point, order quantity, and lead time are the decision variables. Hsiao and Lin (2005) also investigate a SBSV where the vendor holds a monopolistic status and he or she not only owns cost information about the retailer but also has the decision making right of the lead time. For other instances of the SBSV we can refer to Goyal (1988), Goyal and Gupta (1989), and Lu (1995), just to name a few.

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