Design of reverse and forward supply chain network: a case study

Chandiran, P.; Rao, K. Surya Prakasa

doi:10.1504/ijlsm.2008.017601

Cited by 20 publications

(6 citation statements)

References 20 publications

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“…Min et al (2008) employed an MIP and GA to solve the reverse logistics problem involving the consolidation of product returns in e-commerce environments. Chandiran and Rao (2008), and Kannan et al (2009) went a step further from these prior studies by considering a two-way flow coordination/integration of both forward and reverse logistics activities. Also, Du and Evans (2008) considered two conflicting objectives of reverse logistics: costs and tardiness of cycle time.…”

Section: Literature Reviewmentioning

confidence: 99%

A Reverse Logistics Network Model for Handling Returned Products

Zaarour

Melachrinoudis

Solomon

et al. 2014

International Journal of Engineering Business Management

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Due to the emergence of e-commerce and the proliferation of liberal return policies, product returns have become daily routines for many companies. Considering the significant impact of product returns on the company's bottom line, a growing number of companies have attempted to streamline the reverse logistics process. Products are usually returned to initial collection points (ICPs) in small quantities and thus increase the unit shipping cost due to lack of freight discount opportunities. One way to address this issue is to aggregate the returned products into a larger shipment. However, such aggregation increases the holding time at the ICP, which in turn increases the inventory carrying costs. Considering this logistics dilemma, the main objectives of this research are to minimize the total cost by determining the optimal location and collection period of holding time of ICPs; determining the optimal location of a centralized return centre; transforming the nonlinear objective function of the proposed model formulation by Min et al. (2006a) into a linear form; and conducting a sensitivity analysis to the model solutions according to varying parameters such as shipping volume. Existing models and solution procedures are too complicated to solve real-world problems. Through a series of computational experiments, we discovered that the linearization model obtained the optimal solution at a fraction of the time used by the traditional nonlinear model and solution procedure, as well as the ability to handle up to 150 customers as compared to 30 in the conventional nonlinear model. As such, the proposed linear model is more suitable for actual industry applications than the existing models.

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Section: Literature Reviewmentioning

confidence: 99%

A Reverse Logistics Network Model for Handling Returned Products

Zaarour

Melachrinoudis

Solomon

et al. 2014

International Journal of Engineering Business Management

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“…Jayaraman et al (2003) develop a single-period multi-tier MILP that considers EOL product transfers among demand points, collection centres and various treatment plants. Chandiran and Rao (2008) use MILP tools to solve the facility location problem for the closed-loop supply chain network. Salema et al (2007) propose a multi-product problem that considers the recovery demand unpredictability.…”

Section: Literature Reviewmentioning

confidence: 99%

A planning model for the optimisation of the end-of-life vehicles recovery network

Mora

Cascini

Gamberi

et al. 2014

IJLSM

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European Directive 2000/53 on end-of-life vehicles (ELVs) introduced new constraints, regulations and recommendations on the vehicle design, waste disposal and take-back policy. Automotive original equipment manufacturers (OEMs) are even more involved in the expected vehicle recovery network modifications. As a consequence, one of the most critical and C. Mora et al.challenging issues for reverse logistics (RL) management is the development of effective tools to support strategic, tactical and operational decisions to yield the maximum economic benefit in compliance with the reference regulations. In this paper, a mixed integer linear programming (MILP) model for ELV closed-loop network design is proposed. The network cost minimisation objective function, the integration of forward and reverse logistics and the inclusion of remanufacturing activities for vehicle module reuse represent the model key features. The proposed model is, further, applied on a realistic Italian case-study and the results of a sensitivity analysis are presented to identify the parameters most affecting the model outcomes.Reference to this paper should be made as follows: Mora, C., Cascini, A., Gamberi, M., Regattieri, A. and Bortolini, M. (2014) 'A planning model for the optimisation of the end-of-life vehicles recovery network', Int. . His research topics deal with the design and optimisation of complex production (manufacturing) systems and renewable energy systems. In this context his activity is mainly focused on the study and experimentation of solar conversion devices, with particular attention to the technical feasibility and to the economical profitability of concentrating and non-concentrating solar systems.

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“…Salema et al (2007) provided an extension to the MILP model of Fleischmann (2000), by considering capacity limitations, the multi-product case and uncertainty on product demands and returns in a scenario-based manner. Finally, Marin and Pelegrin (1998), Min et al (2005), Yao (2005), Listes (2007), Lu and Bostel (2007), Sahyouni et al (2007) and Chandiran and Rao (2008) also proposed interesting modelling approaches for the closed-loop supply chain network design problem.…”

Section: Literature Backgroundmentioning

confidence: 99%

A strategic methodological optimisation framework for the design of a reverse logistics network with forward supply channel synergies

Xanthopoulos

Iakovou

2010

IJLSM

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Today, an ever increasing number of enterprises undertake significant steps in order to maximise the financial value recovered from End-of-Life (EOL) products, while ensuring sustainable development. In this context, this work deals with the optimal configuration of efficient reverse logistics networks. More specifically, we first present a five-phased strategic methodological model for the development of reverse supply chains. Then, we provide a new mathematical programming model for enterprises that have already structured their forward supply chain and aim at being involved in EOL products' recovery processes. An application of the optimisation model is demonstrated, while obtained managerial insights are discussed.Reference to this paper should be made as follows: Xanthopoulos, A. and Iakovou, E. (2010) 'A strategic methodological optimisation framework for the design of a reverse logistics network with forward supply channel synergies', Int.

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Design of reverse and forward supply chain network: a case study

Cited by 20 publications

References 20 publications

A Reverse Logistics Network Model for Handling Returned Products

A Reverse Logistics Network Model for Handling Returned Products

A planning model for the optimisation of the end-of-life vehicles recovery network

A strategic methodological optimisation framework for the design of a reverse logistics network with forward supply channel synergies

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