• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.79-89
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• 2017

The Optimization of a Closed-Loop Supply Chain (CLSC) Model Using an Adaptive Hybrid Genetic Algorithm (AHGA) Approach is Considered in this Paper. With Forward and Reverse Logistics as an Integrated Logistics Concept, The CLSC Model is Consisted of Various Facilities Such as Part Supplier, Product Manufacturer, Collection Center, Recovery Center, etc. A Mathematical Model and the AHGA Approach are Used for Representing and Implementing the CLSC Model, Respectively. Several Conventional Approaches Including the AHGA Approach are Used for Comparing their Performances in Numerical Experiment.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.63-82
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• 2007

In this paper, we propose an adaptive hybrid genetic algorithm (ahGA) approach for effectively solving multistage-based scheduling problems in flexible manufacturing system (FMS) environment. The proposed ahGA uses a neighborhood search technique for local search and an adaptive scheme for regulation of GA parameters in order to improve the solution of FMS scheduling problem and to enhance the performance of genetic search process, respectively. In numerical experiment, we present two types of multistage-based scheduling problems to compare the performances of the proposed ahGA with conventional competing algorithms. Experimental results show that the proposed ahGA outperforms the conventional algorithms.