2015International Journal of Research in Engineering and TechnologyOpen access

A GENETIC ALGORITHM APPROACH FOR MINIMIZING TOTAL INVENTORY COST IN A JOB-SHOP MANUFACTURING UNIT

Kapil Kumar Gupta .

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Abstract

Inventories are idle resources which are maintained by every organisation for efficient and smooth running of its operations.So here we are going to control the inventory cost by minimizing the inventory cost.For maintaining optimum inventory, one must consider the appropriate reorder point as well as the economic order quantity.We propose an efficient genetic algorithm approach to the find economic order quantity at a proper reorder point.Genetic algorithm is an optimization method used for solving multi-variable optimization problems.Job-shops handle a variety of jobs, where each job is different and different inventory levels are to be maintained.A case study of a power plant where different types of raw materials are used.The proposed approach is tested on C-programme.

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Inventories are idle resources which are maintained by every organisation for efficient and smooth running of its operations.So here we are going to control the inventory cost by minimizing the inventory cost.For maintaining optimum inventory, one must consider the appropriate reorder point as well as the economic order quantity.We propose an efficient genetic algorithm approach to the find economic order quantity at a proper reorder point.Genetic algorithm is an optimization method used for solving multi-variable optimization problems.Job-shops handle a variety of jobs, where each job is different and different inventory levels are to be maintained.A case study of a power plant where different types of raw materials are used.The proposed approach is tested on C-programme.

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Available abstract

Inventories are idle resources which are maintained by every organisation for efficient and smooth running of its operations.So here we are going to control the inventory cost by minimizing the inventory cost.For maintaining optimum inventory, one must consider the appropriate reorder point as well as the economic order quantity.We propose an efficient genetic algorithm approach to the find economic order quantity at a proper reorder point.Genetic algorithm is an optimization method used for solving multi-variable optimization problems.Job-shops handle a variety of jobs, where each job is different and different inventory levels are to be maintained.A case study of a power plant where different types of raw materials are used.The proposed approach is tested on C-programme.

Key concepts: Unit (ring theory), Genetic algorithm, Job shop, Computer science, Operations research, Industrial engineering, Mathematical optimization, Engineering

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