Multi-objective resource assignment problem in a product-driven supply chain using a Taguchi-based DNA algorithm

被引:17
作者
Bachlaus, M. [3 ]
Tiwari, M. K. [2 ]
Chan, F. T. S. [1 ]
机构
[1] Univ Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Hong Kong, Peoples R China
[2] Indian Inst Technol, Dept Ind Engn & Management, Kharagpur 721302, W Bengal, India
[3] NIFFT, Dept Mfg Engn, Ranchi 834003, Bihar, India
关键词
supply chain; resource assignment; nucleotide; hybridisation; fuzzy analytical hierarchical process; multi-objective optimisation; MOLECULAR COMPUTATION; FORMULATION; MANAGEMENT; NETWORK;
D O I
10.1080/00207540701644227
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper conceptualises the integration of tangible and intangible factors into the design consideration of a resource assignment problem for a product-driven supply chain. The problem is formulated mathematically as a multi-objective optimisation model to maximise the broad objectives of profit, ahead of time of delivery, quality, and volume flexibility. Product characteristics are associated with the design requirements of a supply chain. Different types of resources are considered, each differing in its characteristics, thereby providing various alternatives during the design process. The aim is to design integrated supply chains that maximise the weighted sum of the objectives, the weights being decided by the desired product characteristics. The problem is solved through the proposed Taguchi-based DNA algorithm that draws its traits from random search optimisation and the statistical design of experiments. In order to minimise the effect of the causes of variations, the fundamental Taguchi method is integrated with the DNA-metaheuristic. The suggested methodology exhibits the global exploration capability to exploit the optimal or near-optimal DNA strands with a faster convergence rate. In order to authenticate the performance of the proposed solution methodology, a set of ten problem instances are considered and the results obtained are compared with that of the basic DNA, particle swarm optimisation (PSO) and its variant (PSO time varying acceleration coefficients). The results demonstrate the benefits of the proposed algorithm for solving this type of problem.
引用
收藏
页码:2345 / 2371
页数:27
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