Please use this identifier to cite or link to this item:
Title: Optimal supply chain redesign using genetic algorithm
Authors: Kumar Naraharisetti, P.
A. Karimi, I. 
Srinivasana, R. 
Keywords: capacity
genetic algorithms
Issue Date: 2007
Citation: Kumar Naraharisetti, P.,A. Karimi, I.,Srinivasana, R. (2007). Optimal supply chain redesign using genetic algorithm. Computer Aided Chemical Engineering 24 : 703-708. ScholarBank@NUS Repository.
Abstract: Supply chain redesign involves decisions regarding the timing, amount and location attributes of the investment and disinvestment in facilities, production, purchase of raw materials, sale of products, loans and bonds for raising capital, signing of contracts for material purchase and sales, such that the profit is maximized. In this work, we use genetic algorithm to obtain the supply chain redesign plan while maximizing the profit. Genetic algorithms (GA) are best suited for unconstrained problems and we present a novel formulation of the supply chain redesign problem in an unconstrained fashion. To demonstrate this new and unconstrained formulation, we solve the problem which we previously presented (Naraharisetti et al., 2006), where we developed a novel MILP model for supply chain redesign and solved it using Cplex. © 2007 Elsevier B.V. All rights reserved.
Source Title: Computer Aided Chemical Engineering
ISBN: 9780444531575
ISSN: 15707946
DOI: 10.1016/S1570-7946(07)80140-4
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Apr 13, 2019

Page view(s)

checked on Feb 2, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.