A fuzzy-based customer clustering approach with hierarchical structure for logistics network optimization

Wang, Yong; Ma, Xiaolei; Lao, Yunteng; Wang, Yinhai

doi:10.1016/j.eswa.2013.07.078

Cited by 93 publications

(49 citation statements)

References 55 publications

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“…Logistics outsourcing can reduce fixed costs and increase flexibility, allowing for a greater focus on a firm's core activities, a reduction of heavy asset investments and an improvement of service quality (Hsu et al, 2012). At the same time, the decision to outsource includes a number of risks related to the loss of control, long-term commitment and the failures of some LSPs to perform their duties (Farahani et al, 2011;Wang et al, 2014;Soeanu et al, 2015). Table 1 summarises some of the expected advantages and disadvantages of logistics outsourcing: …”

Section: Introductionmentioning

confidence: 99%

A novel technique for evaluating and selecting logistics service providers based on the logistics resource view

Alkhatib

Darlington

Yang

et al. 2015

Expert Systems with Applications

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The increasing importance of logistics outsourcing and availability of logistics services providers (LSPs) highlights the significance and complexity of the LSP evaluation and selection process.Most existing LSP evaluation and selection studies use historical performance data and assume independence among decision criteria. This paper proposes an integrated logistics outsourcing approach to evaluate and select LSPs based on their logistics resources and capabilities. This novel approach combines a fuzzy decision making trial, evaluation laboratory (FDEMATEL) and fuzzy techniques to order preferences by similarity to ideal solution (FTOPSIS) methods.The new multi-criteria decision making (MCDM) model addresses the impact relationships between decision criteria and ranks LSP alternatives against weighted resources and capabilities.The effectiveness of this approach is demonstrated through a real case study and a two-phase sensitivity analysis confirms its robustness.

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Section: Introductionmentioning

confidence: 99%

A novel technique for evaluating and selecting logistics service providers based on the logistics resource view

Alkhatib

Darlington

Yang

et al. 2015

Expert Systems with Applications

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“…Fuzzy numbers are convex and normalized fuzzy sets with a piecewise continuous membership function defined in R that maps an interval to [0, 1]. The use of fuzzy sets and fuzzy numbers has gain attention in the literature mainly for the following reasons: 1) they are able to capture and measure the uncertainty of individual evaluations (20,23,74); 2) fuzzy numbers have a very intuitive meaning and it is more comprehensive than other methods [79]; 3) fuzzy sets can better describe complex processes of the real-life than traditional statistical methods [79]; 4) they can be adapted to a wide range of imprecise data due to the richness of the existing fuzzy scales [23,78,79]. As a consequence, when Likert-type scales, or any other linguistic variables, are used in a questionnaire it is useful to formalize them in terms of fuzzy numbers, in order to reduce the imprecision/vagueness of the observed data.…”

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confidence: 99%

“…For this reason, fuzzy sets, proposed by [77], are a suitable solution to cope with this source of uncertainty [78]. A fuzzy set is defined by a function that assigns to each unit a membership degree.…”

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confidence: 99%

Bagged fuzzy clustering for fuzzy data: An application to a tourism market

D’Urso

Disegna

Massari

et al. 2015

Knowledge-Based Systems

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Segmentation has several strategic and tactical implications in marketing products and services. Despite hard clustering methods having several weaknesses, they remain widely applied in marketing studies. Alternative segmentation methods such as fuzzy methods are rarely used to understand consumer behaviour. In this study, we propose a strategy of analysis, by combining the Bagged Clustering (BC) method and the fuzzy C-means clustering method for fuzzy data (FCM-FD), i.e., the Bagged fuzzy C-means clustering method for fuzzy data (BFCM-FD). The method inherits the advantages of stability and reproducibility from BC and the flexibility from FCM-FD. The method is applied on a sample of 328 Chinese consumers revealing the existence of four segments (Admirers, Enthusiasts, Moderates, and Apathetics) of the perceived images of Western Europe as a tourist destination. The results highlight the heterogeneity in Chinese consumers' place preferences and implications for place marketing are offered.

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“…GA is an evolutionary computing approach used to mimic the natural selection procedure and study combinatorial optimization problems [17,23]. PSO is one of the swarm intelligence stochastic evolutionary metaheuristic approaches, proposed by Kennedy and Eberhart [24].…”

Section: The Hybrid Algorithm Solving Proceduresmentioning

confidence: 99%

Design and Profit Allocation in Two-Echelon Heterogeneous Cooperative Logistics Network Optimization

Wang

Yuan

Assogba

et al. 2018

Journal of Advanced Transportation

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In modern supply chain, logistics companies usually operate individually and optimization researches often concentrate on solving problems related to separate networks. Consequences like the complexity of urban transportation networks and long distance deliveries or pickups and pollution are leading problems to more expenses and more complaints from environment protection organizations. A solution approach to these issues is proposed in this article and consists in the adoption of two-echelon heterogeneous cooperative logistics networks (THCLN). The optimization methodology includes the formation of cooperative coalitions, the reallocation of customers to appropriate logistics facilities, and the determination of the best profit allocation scheme. First, a mixed integer linear programing model is introduced to minimize the total operating cost of nonempty coalitions. Thus, the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm are hybridized to propose GA-PSO heuristics. GA-PSO is employed to provide good solutions to customer clustering units' reallocation problem. In addition, a negotiation process is established based on logistics centers as coordinators. The case study of Chongqing city is conducted to verify the feasibility of THCLN in practice. The grand coalition and two heterogeneous subcoalitions are designed, and the collective profit is distributed based on cooperative game theory. The Minimum Cost Remaining Savings (MCRS) model is used to determine good allocation schemes and strictly monotonic path principles are considered to evaluate and decide the most appropriate coalition sequence. Comparisons proved the combination of GA-PSO and MCRS better as results are found closest to the core center. Therefore, the proposed approach can be implemented in real world environment, increase the reliability of urban logistics network, and allow decision makers to improve service efficiency.

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A fuzzy-based customer clustering approach with hierarchical structure for logistics network optimization

Cited by 93 publications

References 55 publications

A novel technique for evaluating and selecting logistics service providers based on the logistics resource view

A novel technique for evaluating and selecting logistics service providers based on the logistics resource view

Bagged fuzzy clustering for fuzzy data: An application to a tourism market

Design and Profit Allocation in Two-Echelon Heterogeneous Cooperative Logistics Network Optimization

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