The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON ADVANCES in ENGINEERING EDUCATION
Transactions ID Number: 53-109
Full Name: C. Sowmya Danalakshmi
Position: Assistant Professor
Age: ON
Sex: Female
Address: Department of Mechanical Engineering, Karpagam College of Engineering, Coimbatore-641 032
Country: INDIA
Tel: 0422 2619033
Tel prefix:
Fax: 0422 2619046
E-mail address: csowmyadanalakshmi@rediffmail.com
Other E-mails:
Title of the Paper: A framework for optimizing the total operating cost for a manufacturing industry using non-traditional techniques
Authors as they appear in the Paper: C.Sowmya Danalakshmi and Dr.G.Mohankumar
Email addresses of all the authors: csowmyadanalakshmi@rediffmail.com, gmohankumar68@rediffmail.com
Number of paper pages: 10
Abstract: Abstract: Management is a process of integrating and utilizing suppliers, manufacturers, warehouses and retailers, so that goods are produced and delivered at the right quantities and at the right time while minimizing costs as well as satisfying customer requirements. Each manufacturer or distributor has some subset of the supply chain that it must manage and run profitably and efficiently to survive and grow. The primary objective of this work is to optimize the supply chain network of an organization by reducing the total operating cost considering various constraints. The four stages used in this article are suppliers, plants, distribution centers and retailers. Reducing the total operating cost becomes a key factor for the successful business. In this work, the optimal solution of the supply chain networking is obtained by using the non-traditional techniques such as genetic algorithm (GA) and particle swarm optimization algorithm (PSO). Unlike traditional sea!
rch and optimization techniques, allows for the direct incorporation of solutions. After optimizing, the two results were compared and it is found that the proposed genetic algorithm frame work offers a number of advantages like it is a multiple point search technique that examines a set of solutions and not just one solution, it is not derivative based and the stochastic nature of the algorithm helps the search to escape local minima traps when compared to PSO, the exclusive advantage of PSO being with it. The results are submitted to variation with respect to real time environment. In order to monitor and control the real time environment, the post optimality analysis or sensitivity analysis can be conducted.
Keywords: optimization, total operating cost, genetic algorithm, particle swarm optimization and constraints
EXTENSION of the file: .doc
Special (Invited) Session:
Organizer of the Session:
How Did you learn about congress: Optimization Techniques, Supply Chian Managemnt, industrial Engineering, Production operations
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