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Simultaneous improvement of surface quality and productivity using grey relational analysis based Taguchi design for turning couple (AISI D3 steel/ mixed ceramic tool (Al2O3 + TiC))
, Pages: 173-194 Oussama Zerti, Mohamed Athmane Yallese, Abderrahmen Zerti, Salim Belhadi and Francois Girardin PDF (685K) |
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Abstract: Current optimization strategies are based on the increase the productivity and the quality with lower cost in short time. Grey relational analysis “GRA” based on Taguchi design was proposed in this paper for simultaneous improvement of surface quality and productivity. The turning trials based on mixed Taguchi L18 factorial plan were conducted under dry cutting conditions for the machining couple: AISI D3 steel/mixed ceramic inserts (CC650). The machining parameters taken into account during this study are as follow: major cutting edge angle (χr), cutting insert nose radius (r), cutting speed (Vc), feed rate (f), and depth of cut (ap). Significant effects of machining parameters and their interactions were evaluated by the analysis of variance. Through this analysis, it have been found clearly that feed rate and cutting insert nose radius had a big significant effects on surface quality while depth of cut, feed rate followed by cutting speed had a major effect on productivity. The mathematical relationship between the machining parameters and the performance characteristics was formulated by using a linear regression model with interactions. Optimal levels of parametric combination for achieving the higher surface quality with maximum productivity were selected by grey relational analysis which is based on the high value of grey relational grade. Confirmation experiments were carried out to prove the powerful improvement of experimental results and to validate the effectiveness of the multi-optimization technique applied in this paper. DOI: 10.5267/j.ijiec.2017.7.001 Keywords: Simultaneous improvement, GRA, Taguchi design, S/N ratio, ANOVA, AISI D3 Steel, Ceramic
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Variable neighborhood search algorithm for the green vehicle routing problem
, Pages: 195-204 Mannoubia Affi, Houda Derbel and Bassem Jarboui PDF (685K) |
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Abstract: This article discusses the ecological vehicle routing problem with a stop at a refueling station titled Green-Vehicle Routing Problem. In this problem, the refueling stations and the limit of fuel tank capacity are considered for the construction of a tour. We propose a variable neighborhood search to solve the problem. We tested and compared the performance of our algorithm intensively on datasets existing in the literature. DOI: 10.5267/j.ijiec.2017.6.004 Keywords: Green vehicle routing problem, Refueling stations, Variable neighborhood search, Heuristics
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Pricing and lot sizing optimization in a two-echelon supply chain with a constrained Logit demand function
, Pages: 205-220 Yeison Díaz-Mateus, Bibiana Forero Héctor López-Ospina and Gabriel Zambrano-Rey PDF (685K) |
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Abstract: Decision making in supply chains is influenced by demand variations, and hence sales, purchase orders and inventory levels are therefore concerned. This paper presents a non-linear optimization model for a two-echelon supply chain, for a unique product. In addition, the model includes the consumers’ maximum willingness to pay, taking socioeconomic differences into account. To do so, the constrained multinomial logit for discrete choices is used to estimate demand levels. Then, a metaheuristic approach based on particle swarm optimization is proposed to determine the optimal product sales price and inventory coordination variables. To validate the proposed model, a supply chain of a technological product was chosen and three scenarios are analyzed: discounts, demand segmentation and demand overestimation. Results are analyzed on the basis of profits, lotsizing and inventory turnover and market share. It can be concluded that the maximum willingness to pay must be taken into consideration, otherwise fictitious profits may mislead decision making, and although the market share would seem to improve, overall profits are not in fact necessarily better. DOI: 10.5267/j.ijiec.2017.6.003 Keywords: Constrained multinomial logit, Pricing, Lotsizing, Supply chain optimization, PSO
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Parameters optimization of fabric finishing system of a textile industry using teaching–learning-based optimization algorithm
, Pages: 221-234 Rajiv Kumar, P.C. Tewari and Dinesh Khanduja PDF (685K) |
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Abstract: In the present work, a recently developed advanced optimization algorithm named as teaching–learning-based optimization (TLBO) is used for the parameters optimization of fabric finishing system of a textile industry. Fabric Finishing System has four main subsystems, arranged in hybrid configuration. For performance modeling and analysis of availability, a performance evaluating model of fabric finishing system has been developed with the help of mathematical formulation based on Markov-Birth-Death process using Probabilistic Approach. Then, the overall performance of the concerned system has first analyzed and then, optimized by using teaching–learning-based optimization (TLBO). The results of optimization using the proposed algorithm are validated by comparing with those obtained by using the genetic algorithm (GA) on the same system. Improvement in the results is obtained by the proposed algorithm. The results of effect of variation of the algorithm parameters on fitness values of the objective function are reported. DOI: 10.5267/j.ijiec.2017.6.002 Keywords: Performance modeling, TLBO, Markov process, Genetic algorithm, Probabilistic Approach
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Alternative fabrication scheme to study effects of rework of nonconforming products and delayed differentiation on a multiproduct supply-chain system
, Pages: 235-248 Yuan-Shyi Peter Chiu, Hong-Dar Lin, Mei-Fang Wu and Singa Wang Chiu PDF (685K) |
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Abstract: This study uses an alternative fabrication scheme to study the effect of rework of nonconforming items and delayed differentiation on a multiproduct supply-chain system. Traditional economic production quantity model focuses on a single-product inventory system where all products made are assumed to be perfect quality and finished products are issued continuously. To increase machine utilization, lower quality costs in production, and reflect the real-world vendor-buyer integrated systems Chiu et al. (2016a) [Chiu, Y-S.P., Kuo, J-S., Chiu, S. W., Hsieh, Y-T. (2016a). Effect of delayed differentiation on a multiproduct vendor–buyer integrated inventory system with rework. Advances in Production Engineering & Management, 11(4), 333-344.] employed a single-machine two-stage production scheme to study the effects of rework and delayed differentiation on a multi-product supply-chain system. With the intention of further reducing fabrication cycle time, this study considers an alternative two-machine two-stage fabrication scheme to re-explore the problem in Chiu et al. (2016a). Machine one solely produces all common parts for multiple end products. Then, machine two fabricates the customized multiproduct using a common cycle time strategy. Through the use of mathematical modeling and analyses, the optimal production cycle length and distribution policy are derived. Numerical examples are provided to demonstrate practical usage of the research results, and show its significant benefit in reducing fabrication cycle time compared to that obtained from prior studies that used different schemes. DOI: 10.5267/j.ijiec.2017.6.001 Keywords: Multiproduct system, Cleaner production, Rework of nonconforming items, Delay product differentiation, Two-machine scheme, Multi-delivery plan
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Dynamic capacitated maximal covering location problem by considering dynamic capacity
, Pages: 249-264 Jafar Bagherinejad and Mahnaz Shoeib PDF (685K) |
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Abstract: Capacitated maximal covering location problems (MCLP) have considered capacity constraint of facilities but these models have been studied in only one direction. In this paper, capacitated MCLP and dynamic MCLP are integrated with each other and dynamic capacity constraint is considered for facilities. Since MCLP is NP-hard and commercial software packages are unable to solve such problems in a rational time, Genetic algorithm (GA) and bee algorithm are proposed to solve this problem. In order to achieve better performance, these algorithms are tuned by Taguchi method. Sample problems are generated randomly. Results show that GA provides better solutions than bee algorithm in a shorter amount of time. DOI: 10.5267/j.ijiec.2017.5.004 Keywords: Capacitated MCLP, Multi-period MCLP, Dynamic capacity, Genetic algorithm, Bee algorithm
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