Using fuzzy analytic hierarchy process and particle swarm optimisation for balanced and defective supply chain problems considering WEEE/RoHS directives

H., Z.

doi:10.1080/00207540802702080

Cited by 71 publications

(31 citation statements)

References 42 publications

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“…To examine the suppliers from a broader perspective, recent researches have considered multiple factors in supplier evaluation [19][20][21]17,18,[22][23][24][25]. Liaoa and Rittscherb [22] used cost, quality, and delivery time as the factors in supplier evaluation under the inventory mode.…”

Section: Clustering Of Suppliersmentioning

confidence: 99%

A hybrid approach for supplier cluster analysis

Wang

2010

Computers & Mathematics with Applications

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a b s t r a c tTo differentiate part suppliers effectively, this study proposed a hybrid approach based on K -means, simulated annealing algorithm (SA), convergence factor particle swarm optimization (CPSO), and the Taguchi method abbreviated as KSACPSO. After all parts suppliers are confirmed by the bill of material (BOM), supplier cluster analysis was conducted on characteristics of customers' demands, including product cost, product quality, and procurement time using the proposed approach. To prove the KSACPSO approach has good clustering performance, the case study of a notebook computer was adopted to carry out the clustering procedures on parts suppliers, and compare the differences between the proposed approach and other hybrid methods. The execution results were analyzed to prove that the efficiency of the suggested KSACPSO approach is superior to K -means, K -means simulated annealing (KSA), K -means genetic algorithm (KGA), K -means genetic simulated annealing (KGSA), and K -means convergence factor particle swarm optimization (KCPSO).

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Section: Clustering Of Suppliersmentioning

confidence: 99%

A hybrid approach for supplier cluster analysis

Wang

2010

Computers & Mathematics with Applications

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“…AHP can also be clubbed with heuristics, meta-heuristics, and other problem solving tools efficiently. Wang et al [12] and Che [13] used AHP for framing weights to solve multi-criteria problems using PSO. But a complete integration with PSO algorithm was not done.…”

Section: Pso Algorithm Ga and Ahpmentioning

confidence: 99%

“…To the best of the authors' knowledge, simulation approach is integrated with AHP and DPSO algorithm for the first time in this research. Earlier, AHP was used for framing weights to solve multi-criteria problems using particle swarm optimization (PSO) by Wang et al [12] and Che [13]. AHP was used for determining criteria weights alone, and a complete integration with PSO algorithm was not carried out.…”

Section: Introductionmentioning

confidence: 99%

Development of simulation-based AHP-DPSO algorithm for generating multi-criteria production–distribution plan

Varthanan¹,

Murugan²,

Kumar

et al. 2011

Int J Adv Manuf Technol

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Integrated production-distribution plan considering three major objectives, viz., total cost minimization, change in labor level reduction, and underutilization minimization, is developed for a renowned bearing manufacturing industry in India. The total cost minimization objective minimizes the regular, overtime, and outsourced production costs along with inventory holding, backorder, hiring/layingoff, and trip-wise distribution costs. The multi-criteria model is solved using a novel simulation-based analytic hierarchy process (AHP)-discrete particle swarm optimization (DPSO) algorithm. The solutions of the AHP-DPSO algorithm are verified using the AHP-binary-coded genetic algorithm solutions. The proposed simulation-based AHP-DPSO solutions are found to be superior. Demand is assumed to vary uniformly, and the simulation-based AHP-DPSO algorithm is used for obtaining the best production-distribution plan that serves as a trade-off between holding inventory and backordering products. In addition to bearing manufacturing industry dataset, two other test datasets are also solved.

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“…Thanaraksakul and Phruksaphanrat (2009) surveyed 76 papers on supplier selection in the purchasing literature and found that price, quality and delivery were the most commonly listed supplier evaluation dimensions. Che (2010) stated that the selection of quality suppliers from a large pool of potential suppliers was a very important factor in supply chain decisionmaking. He proposed an optimization mathematical model and a heuristic method to evaluate suppliers in a multi-echelon supply chain system using cost, time, quality and environmental criteria.…”

Section: Introductionmentioning

confidence: 99%