Solving a Public Sector Sustainable Supply Chain Problem : A Genetic Algorithm Approach

This paper addresses a sustainable supply chain network design problem that arises in the public sector. There is little research being done in mathematical modeling and solutions methods for these problems. The paper describes a mixed-integer 0-1 model (MIP) for solving this sustainable problem in which we have to determine a fixed number of facilities to be located at sites chosen from among a given set of candidate sites. Sustainable issues are integrated into the model by reducing the greenhouse gas emissions produced by the transportation and the operation of the facilities. We propose a hybrid genetic algorithm (GA) for solving this problem by introducing a greedy-like procedure during the feasibility phase. In order to validate our GA solutions we used GAMS to obtain optimal objective values on the MIP. We report computational results for instances generated from a known OR test library.

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