Multiobjective Analysis of the Multi-Location Newsvendor and Transshipment Models

Multiobjective Analysis of the Multi-Location Newsvendor and Transshipment Models

Nabil Belgasmi (National School of Computer Sciences, University of Manouba, Manouba, Tunisia & SOIE Laboratory (Stratégies d'Optimisation et Informatique Intelligente), Le Bardo, Tunisia), Lamjed Ben Saïd (SOIE Laboratory (Stratégies d'Optimisation et Informatique Intelligente), Le Bardo, Tunisia) and Khaled Ghédira (SOIE Laboratory (Stratégies d'Optimisation et Informatique Intelligente), Le Bardo, Tunisia)
DOI: 10.4018/ijisscm.2013100103
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Abstract

Unlike the Newsvendor model, a system based on lateral transshipments allows the unsold inventories to be moved from locations with surplus inventory to fulfill more unmet demands at stocked out locations. Both models were thoroughly studied and researches were usually confined to cost minimization or profit maximization. In this paper, the authors proposed a more realistic multiobjective study of both multi-location Transshipment and Newsvendor inventory models. The aggregate cost, the fill rate, and the shared inventory quantity are formulated as conflicting objectives and solved using two reference multiobjective evolutionary algorithms (SPEA2 and NSGA-II). The proposed models take into account the presence of storage capacity constraints. The obtained Pareto fronts revealed interesting information. When transshipments are allowed, both low aggregate cost and high fill rate levels are ensured. The required shared inventory may have an important variability. The considered objective functions are conflicting and very sensitive to local storage capacities.
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Literature Review

There is a considerable amount of Supply Chain Management in the last past decades. Some papers provided interesting surveys. Pokharel (2008) indicated that various objectives could be considered for strategic decision making on Supply Chain Network: (1) increasing service level, (2) decreasing warehouse costs, (3) decreasing total fixed and variable costs, (4) decreasing lead time (order processing and supply lead times), (5) consolidating supplier base, (6) increasing supplier reliability, (7) increasing capacity utilization and, (8) increasing total quality of supply. In the same work, Pokharel (2008) developed a two-objective decision-making model for the choice of suppliers and warehouses for a supply chain network design. Arshinder et al. (2008) presented a systematic literature review on the importance of Supply Chain coordination. They reported various perspectives on Supply chains coordination issues and explained various mechanisms available for coordination.

Multiple objectives were investigated and diverse optimization approaches were used. Liao and Rittscher (2007) simultaneously considered the optimization of the total cost, the quality rejection rate, the late delivery rate and the flexibility rate in their stochastic supplier selection problem while involving constraints of demand satisfaction and capacity. Zhou et al. (2003) studied the bi-criteria allocation problem involving multiple warehouses with different capacities using a genetic algorithm based solution procedure. Liberopoulos and Koukoumialos (2005), numerically investigated tradeoffs between near-optimal base stock levels, numbers of kanbans, and planned supply lead times in base stock policies and hybrid base stock/kanban policies.

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