A genetic algorithm for minimizing energy consumption in warehouses

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Date

2016-11-01

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Pergamon-Elsevier Science

Abstract

Green supply chain Management is generally defined as integration of green thinking and environmental issues into the whole supply chain operations like product design, manufacturing process, warehousing, distribution etc. Within this context green principles should be adopted in warehouse management to minimize negative impact on the environment. In warehouse operations, picking must be analyzed attentively which is widely studied in literature for minimizing service time levels because of its close relation to the higher costs. The efficiency of picking in warehouses mainly depends on storage assignment policy that directly affects picking performance in warehouses. In this paper, picking operation in warehouses is studied to minimize energy consumption with proper storage policy other than service time. Genetic algorithm (GA) is proposed to solve the problem and numerical examples are presented to demonstrate the performance of the GA. Results show that, the GA gives efficient solutions to the problem.

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Keywords

Thermodynamics, Energy & fuels, Genetic algorithm, Green supply chain, Minimization of energy consumption, Warehouse management, Order-picking, Storage assignment, Travel distance, Policies, Design, Green, Algorithms, Energy policy, Energy utilization, Genetic algorithms, Industrial management, Product design, Supply chain management, Environmental issues, Green supply chain, Green supply chain management, Impact on the environment, Manufacturing process, Storage assignment policies, Supply chain operation, Warehouse management, Energy conservation, Environmental issue, Genetic algorithm, Manufacturing, Supply chain management, Warehouses

Citation

Ene, S. vd. (2016). "A genetic algorithm for minimizing energy consumption in warehouses". Energy, 114, 973-980.