Joint optimization of product family design and supplier selection under multinomial logit consumer choice rule

Cao, Yan; Luo, Xinggang; Kwong, C. K.; Tang, Jiafu; Zhou, Wei

doi:10.1177/1063293x12468456

Cited by 32 publications

(14 citation statements)

References 24 publications

(31 reference statements)

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“…Luo et al [26] investigated the concurrent optimization method of product family design and supplier selection in consideration of the choice behavior of a consumer. Cao et al [27] presented a technique to optimize product family design and supplier selection under the multinomial logit consumer choice rule. Khalaf et al [28] adopted a tabu search algorithm to configure product lines in consideration of time limits and assembly line constraints.…”

Section: Product Family Designmentioning

confidence: 99%

“…The following basic assumptions were used in this research. (1) The total market can be divided into several market segments, and the purchase preferences of the customers in the same market segment were considered as the same [27]. (2) The candidate instances of each module had the same interface, and thus they can replace each other [27].…”

Section: Problem Presentationmentioning

confidence: 99%

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A Concurrence Optimization Model for Low-Carbon Product Family Design and the Procurement Plan of Components under Uncertainty

Wang

2021

Sustainability

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With the increase in pollution and people’s awareness of the environment, reducing greenhouse gas (GHG) emissions from products has attracted more and more attention. Companies and researchers are seeking appropriate methods to reduce the GHG emissions of products. Currently, product family design is widely used for meeting the diverse needs of customers. In order to reduce the GHG emission of products, some methods for low-carbon product family design have been presented in recent years. However, in the existing research, the related GHG emission data of a product family are given as crisp values, which cannot assess GHG emissions accurately. In addition, the procurement planning of components has not been fully concerned, and the supplier selection has only been considered. To this end, in this study, a concurrence optimization model was developed for the low-carbon product family design and the procurement plan of components under uncertainty. In the model, the relevant GHG emissions were considered as the uncertain number rather than the crisp value, and the uncertain GHG emissions model of the product family was established. Meanwhile, the order allocation of the supplier was considered as the decision variable in the model. To solve the uncertain optimization problem, a genetic algorithm was developed. Finally, a case study was performed to illustrate the effectiveness of the proposed approach. The results showed that the proposed model can help decision-makers to simultaneously determine the configuration of product variants, the procurement strategy of components, and the price strategies of product variants based on the objective of maximizing profit and minimizing GHG emission under uncertainty. Moreover, the concurrent optimization of low-carbon product family design and order allocation can bring the company greater profit and lower GHG emissions than just considering supplier selection in low-carbon product family design.

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Section: Product Family Designmentioning

confidence: 99%

Section: Problem Presentationmentioning

confidence: 99%

A Concurrence Optimization Model for Low-Carbon Product Family Design and the Procurement Plan of Components under Uncertainty

Wang

2021

Sustainability

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“…A model of integrating supplier selection with product family design was formulated and solved by a linear programming embedded genetic algorithm [6]. A nonlinear optimization model under multinomial logit consumer choice rule for the integrated problem was also formulated [7]. Balakrishnan and Chakravarty [8] studied the integration of product variants and supplier selection as a profit-driven decision making problem.…”

Section: Introductionmentioning

confidence: 99%

A cooperative negotiation embedded NSGA-II for solving an integrated product family and supply chain design problem with remanufacturing consideration

Kwong

Aydın

et al. 2017

Applied Soft Computing

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Product family design is a popular approach adopted by manufacturers to increase their product varieties in order to satisfy the needs of various markets. In recent years, because of increasing environmental concerns in societies and strict regulations of environmental protection, quite a number of manufacturers adopted remanufacturing strategy in their product development in response to the challenges. Remanufacturing of used products unavoidably involves a closed-loop supply chain system. To achieve the best outcomes, the supply chain design should be considered in product family design process. In this research, a multiobjective optimization model of integrated product family and closed loop supply chain design is formulated based on a cooperative game model for minimizing manufacturer"s total cost and maximize suppliers" total payoffs. Since the optimization problem could be a largescale one and involves mixed continuous-discrete variables, a new version of nondominated sorting genetic algorithm-II (NSGA-II), namely cooperative negotiation embedded NSGA-II (NSGA-CO), is proposed to solve the optimization model. Simulation tests are conducted to validate the effectiveness of the proposed NSGA-CO. The test results indicate that the proposed NSGA-CO outperforms NSGA-II in solving various scale of multi-objective optimization problems in terms of convergence. With the formulated optimization model and the proposed NSGA-CO, a case study of integrated product family and supply chain design is conducted to investigate the effects of environmental penalty, quantity of demand and marginal cost of remanufacturing on used product return rate, manufacturers" and suppliers" profits and joint payoff.

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“…Balakrishnan and Chakravarty (2008) presented a method that, with a focus on reducing cost, explicitly coupled product choice and vendor selection to assist product design with multiple suppliers for component variants. Cao et al (2012) developed a genetic algorithm and presented a method to jointly optimize product family design and supplier selection with the relatively small-sized printing calculator product case presented in Luo et al (2011).…”

Section: Introductionmentioning

confidence: 99%

On a methodology for component selection in modular branding: An industrial pilot study

Börjesson¹,

Fancher

Sellgren

2014

Concurrent Engineering

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Performing modularization of a product family with multiple brands is a complex task that must integrate and balance a wide range of contradicting and ambiguous aspects, such as product performance, customer expectations, supplier alliances, and corporate business strategies. Furthermore, decisions on balancing these aspects that also change with time have to deal with a high degree of uncertainty. No general methodology for modular branding has currently been published. A methodology with that aim is proposed and prototyped in a real but anonymized industrial case. The presented task is to select standard original equipment manufacturer engines for six brands of self-propelled walk-behind lawn mowers. Selection is based on a set of calculated utility scores and known costs. The utility of an engine with a certain performance level and set of features is specific to each brand. This article presents a first step in developing a general methodology for modular branding and the organizational learnings of using the proposed methodology in an industrial setting.

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Joint optimization of product family design and supplier selection under multinomial logit consumer choice rule

Cited by 32 publications

References 24 publications

A Concurrence Optimization Model for Low-Carbon Product Family Design and the Procurement Plan of Components under Uncertainty

A Concurrence Optimization Model for Low-Carbon Product Family Design and the Procurement Plan of Components under Uncertainty

A cooperative negotiation embedded NSGA-II for solving an integrated product family and supply chain design problem with remanufacturing consideration

On a methodology for component selection in modular branding: An industrial pilot study

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