Optimizing Inventory Using Genetic Algorithm for Efficient Supply Chain Management

Problem statement: Today, inventory management is considered to be an important field in Supply chain management. Once the efficient and effective management of inventory is carried out throughout the supply chain, service provided to the customer ultimately gets enhanced. Hence, to ensure minimal cost for the supply chain, the determination of the level of inventory to be held at various levels in a supply chain is unavoidable. Minimizing the total supply chain cost refers to the reduction of holding and shortage cost in the entire supply chain. Efficient inventory management is a complex process which entails the management of the inventory in the whole supply chain and getting the final solution as an optimal one. In other words, during the process of supply chain management, the stock level at each member of the supply chain should account to minimum total supply chain cost. The dynamic nature of the excess stock level and shortage level over all the periods is a serious issue when implementation was considered. In addition, consideration of multiple products leads to very complex inventory management process. The complexity of the problem increases when more distribution centers and agents were involved. Approach: In present research, the issues of inventory management had been focused and a novel approach based on genetic algorithm had been proposed in which the most probable excess stock level and shortage level required for inventory optimization in the supply chain is distinctively determined so as to achieve minimum total supply chain cost. Results: The analysis provided us with an inventory level that made a remarkable contribution towards the increase of supply chain cost. We predicted the optimal inventory levels in all the supply chain members with the aid of these levels. Conclusion: We concluded that it is possible to minimize the supply chain cost by maintaining the optimal stock levels that we predicted from the inventory analysis. This will make the inventory management further effective and efficient thereby enhancing the customer servicing levels.

[1]  Pupong Pongcharoen,et al.  Multi-matrix Real-coded Genetic Algorithm for Minimising Total Costs in Logistics Chain Network , 2007 .

[2]  João Caldeira,et al.  Supply-Chain Management Using ACO and Beam-ACO Algorithms , 2007, 2007 IEEE International Fuzzy Systems Conference.

[3]  Caro Lucas,et al.  An Innovative Fuzzy Decision Making Based Genetic Algorithm , 2008 .

[4]  Aphirak Khadwilarda,et al.  APPLICATION OF GENETIC ALGORITHM FOR TRAJECTORY PLANNING OF TWO DEGREE-OF-FREEDOM ROBOT ARM WITH TWO DIMENSIONS , 2006 .

[5]  Saifuddin Md. Tareeq,et al.  Robust Face Detection using Genetic Algorithm , 2007 .

[6]  Michael J. Magazine,et al.  A Taxonomic Review of Supply Chain Management Research , 1999 .

[7]  C.M. Adams Inventory optimization techniques, system vs. item level inventory analysis , 2004, Annual Symposium Reliability and Maintainability, 2004 - RAMS.

[8]  Ali Asghar Alesheikh,et al.  Developing a Genetic Algorithm to Solve Shortest Path Problem on a Raster Data Model , 2008 .

[9]  Hau L. Lee,et al.  The Evolution of Supply-Chain-Management Models and Practice at Hewlett-Packard , 1995 .

[10]  S. Buffett,et al.  An Algorithm for Procurement in Supply-Chain Management , 2022 .

[11]  S. Mirza,et al.  Fitness Function Evaluation for Image Reconstruction using Binary Genetic Algorithm for Parallel Ray Transmission Tomography , 2006, 2006 International Conference on Emerging Technologies.

[12]  M. R. Gopalan Inventory Optimization in Supply Chain Management using Genetic Algorithm , 2009 .

[13]  Kesheng Wang,et al.  Applying Genetic Algorithms to Optimize the Cost of Multiple Sourcing Supply Chain Systems – An Industry Case Study , 2008 .

[14]  Hui Gao,et al.  Air material inventory optimization model based on genetic algorithm , 2000, Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393).

[15]  Jeffrey A. Joines,et al.  Supply chain multi-objective simulation optimization , 2002, Proceedings of the Winter Simulation Conference.

[16]  David B. Shmoys,et al.  Approximation Algorithms for Stochastic Inventory Control Models , 2005, Math. Oper. Res..

[17]  Franz Rothlauf,et al.  Developing Genetic Algorithms and Mixed Integer Linear Programs for Finding Optimal Strategies for a Student’s “Sports” Activity , 2006 .

[18]  Pupong Pongcharoen,et al.  Application of Genetic Algorithm for Trajectory Planning of Two Degrees of Freedom Robot Arm With Dimensions , 2007 .

[19]  B. Beamon Supply chain design and analysis:: Models and methods , 1998 .

[20]  Luis Rabelo,et al.  Stability analysis of the supply chain by using neural networks and genetic algorithms , 2007, 2007 Winter Simulation Conference.

[21]  Péter MILEFF,et al.  A NEW INVENTORY CONTROL METHOD FOR SUPPLY CHAIN MANAGEMENT , 2006 .

[22]  Maged Dessouky,et al.  A genetic algorithm approach to the integrated inventory-distribution problem , 2006 .

[23]  David P. Stone An Autonomous Agent for Supply Chain Management , 2007 .

[24]  Mohsen Soryani,et al.  Application of Genetic Algorithms to Feature Subset Selection in a Farsi OCR , 2008 .