OPTIMIZATION OF BIN PACKING PROBLEMS USING META HEURISTIC APPROACH
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In a recent economical competitive environment, the firms reduce their product cost without compromising the quality. This research work concentrates on the perfect packing of goods into the container by considering major practical constraints using an evolutionary algorithm, which is essential for a firm to survive in today's competitive globalized environment. This research is done with few assumptions and constraints by considering the reality of logistics. A Fisherman Based Heuristic Approach (FBHA) and a Sheep Flock Based Meta-Heuristic Approach (SFBMHA) have been developed to solve the b...
In a recent economical competitive environment, the firms reduce their product cost without compromising the quality. This research work concentrates on the perfect packing of goods into the container by considering major practical constraints using an evolutionary algorithm, which is essential for a firm to survive in today's competitive globalized environment. This research is done with few assumptions and constraints by considering the reality of logistics. A Fisherman Based Heuristic Approach (FBHA) and a Sheep Flock Based Meta-Heuristic Approach (SFBMHA) have been developed to solve the bin packing problem. In further, Genetic Algorithm (GA) Integrated Approaches (GAIAs) are defined as the combined approach of heuristic/metaheuristic and optimization technique. The proposed FBHA, SFBMHA, and GAIAs have to be validated through standardized problems to determine the efficiency of the methodologies. The GAIAs are better to FBHA and SFBMHA by the integration genetic algorithm, which about 4.5% and 4% respectively in achieving effective space utilization. The processing time to achieve the above effectiveness is around 4 and 11 seconds for GAIA-I and GAIA-II respectively.
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