• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.383-397
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• 2014

Reverse logistics network design issues have been popularly discussed in recent years. However, few papers in the past literature have been dedicated to incentive effect on return quantity of used products. The purpose of this study is to formulate a dynamic nonlinear programming model of reverse logistics network design with the aim of managing the used products allocation by coordinating the collection centers and recovery facilities to warrant economic efficiency. In the optimization model, a fuzzy approach is applied to interpret the relationship between the rate of return and the suggested incentives. Due to funding constraints in setting up the collection centers, this work considers these centers as multi-capacity levels, which can be opened or closed at different periods. In view of the fact that the problem is known as NP-hard, we propose a heuristic method based on tabu search procedure to solve the presented model. Finally, several dominance properties of optimal solutions are demonstrated in comparison with the results of a state-of-the-art commercial solver.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.53-64
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• 2019

The term 're-use' here signifies the re-use of end-of-life products without changing their form after they have been thoroughly inspected and cleaned. In the re-use network model, the distributor determines the product order quantity on the network through which new products are received from the suppliers or products are supplied to the customers through re-use of the recovered products. In this paper, we propose a reusable network model for reusable products that considers the total logistics cost from the forward logistics to the reverse logistics. We also propose a reusable network model that considers the processing and disposal costs for reuse in an optimal inventory management environment. The authors employe Genetic Algorithm (GA), which is one of the optimization techniques, to verify the validity of the proposed model. And in order to investigate the effect of the parameters on the solution, the priority-based GA (priGA) under three different parameters and the modified Hybrid GA (mhGA), in which parameters are adjusted for each generation, were applied to four examples with varying sizes in the simulation.

• Korea Trade Review
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• v.45 no.3
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• pp.1-19
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• 2020

Recently, traditional trade in the global trade market has stagnated in the aftermath of the US-China trade war and the coronavirus (COVID-19) pandemic. However, the global e-commerce market is growing rapidly, presenting a new opportunity for exports. To examine the effect of an online matching and logistics system on reverse overseas direct purchase and the mediating effect of reliability, this study conducted a questionnaire survey on 320 employees in a Korean trade company from March 10 to April 30, 2018. The study model's goodness of fit was tested, and an analysis was performed using the AMOS statistical package. The online matching and logistics system were found to have a positive effect on reverse overseas direct purchase. Furthermore, results revealed that while a country's reliability mediated online matching and reverse overseas direct purchase, it did not mediate the logistics system. These results mean that online matching is affected by a country's reliability in overseas consumers' buying decision process. This study provides implications for the future directions of export companies and national policies to promote reverse overseas direct purchase. Future research including more countries and companies would be able to make further contributions toward the development of the Korean cross-border e-commerce industry.

• Journal of the Korea Safety Management & Science
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• v.17 no.3
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• pp.239-246
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• 2015

Enforced environmental regulations call for extending the domain of manufacturers' responsibility to the entire product life cycle. To comply with the environmental regulations, manufacturers have constructed reverse logistics networks to re-collect their leftover waste for recycling consumed resources. However, the operational activities associated with storage, loading and transportation processes within the networks inevitably impose environmental burdens. Particularly, the transportation process largely influences environmental performance due to perpetual uses of transportation vehicles. Therefore, there is a need to develop an environmentally-conscious transportation model that can efficiently manage the uses of transportation vehicles. Additionally, it is vital to analyze its significances of environmental performance to compare quantitatively it with existing models. This paper proposes a transportation model for improving environmental performance in a reverse logistics network. This paper also presents a case study to perform its comparative analysis using Life Cycle Assessment that evaluates potential environmental impacts of a product system.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.97-104
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• 2010

Expanded muti-source Weber problem (EWP), which introduced in this paper, is a reverse logistics network design problem to minimize the total transportation cost from customers thorough regional center to central center. Decision factor of EWP are the locations of regional centers and a central center. We introduce a GRASP heuristics for the EWP. In the suggested GRASP, an expanded iterative location allocation method (EILA) is introduced based on the Cooper's iterative location allocation method[3]. For the initial solution of GRASP, allocation first seed (AFSeed) and location first seed (LFSeed) are developed. The computational experiment for the objective value shows that the LFSeed is better than the AFSeed. Also the calculating time of the LFSeed is better than that of the AFSeed.

• Korean Management Science Review
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• v.27 no.3
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• pp.15-31
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• 2010

We consider a reverse logistics network design problem for recycling. The problem consists of three stages of transportation. In the first stage products are transported from retrieval centers to disassembly centers. In the second stage disassembled modules are transported from disassembly centers to processing centers. Finally, in the third stage modules are transported from either processing centers or a supplier to a manufacturer, a recycling site, or a disposal site. The objective is to design a network which minimizes the total transportation cost. We design a cooperative coevolutionary algorithm to solve the problem. First, the problem is decomposed into three subproblems each of which corresponds to a stage of transportation. For subproblems 1 and 2, a population of chromosomes is constructed. Each chromosome in the population is coded as a permutation of integers and an algorithm which decodes a chromosome is suggested. For subproblem 3, an heuristic algorithm is utilized. Then, a performance evaluation procedure is suggested which combines the chromosomes from each of two populations and the heuristic algorithm for subproblem 3. An experiment was carried out using test problems. The experiments showed that the cooperative coevolutionary algorithm generally tends to show better performances than the previous genetic algorithm as the problem size gets larger.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.45-66
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• 2008

Refuse collection, one of important elements in reverse logistics, is an activity rendering recyclables or wastes and moving them to some points where further treatment is required. Among various decisions in the collection activity, we focus on network design, which is the problem of locating collection points as well as allocating refuses at demand points to collection points while satisfying the capacity restriction at each collection point. Here, the collection point is the place where recyclables or wastes near the point are gathered, and locating the collection points is done by selecting them from a given set of potential sites. The objective is to minimize the sum of fixed costs to open collection points and transportation costs to move refuses from demand points to collection points. An integer programming model is developed to represent the problem mathematically and due to the complexity of the problem, two types of heuristics, one with simultaneous and the others with separate location and allocation, are suggested. Computational experiments were done on test problems up to 500 potential sites, and the results are reported. In particular, some heuristics gave near optimal solutions for small-size test problems, i.e., 2% gaps in average from the optimal solution values.

• IE interfaces
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• v.20 no.2
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• pp.154-161
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• 2007

When the electrical appliances such as TVs and refrigerators become obsolete, they must be collected to the recycling centers to avoid environmental damages. The obsolete home appliances are first moved to the regional collection point; and then transported to one of the recycling centers. Each recycling center has a limited capacity; and some recycling centers can process only certain types of products. For given locations of the existing collection points and recycling centers, optimally assigning the obsolete home appliances of each type from each collection point to the recycling centers can significantly reduce the total transportation cost. We formulate this problem as an LP problem. We also present an approach to determine the locations of additional recycling centers in order to alleviate the over-utilization of the current recycling centers.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.4
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• pp.31-41
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• 2016

This paper is to evaluate the performance of a proposed hybrid genetic algorithm (pro-HGA) approach using closed-loop supply chain (CLSC) model. The proposed CLSC model is a integrated supply chain network model both with forward logistics and reverse logistics. In the proposed CLSC model, the reuse, resale and waste disposal using the returned products are taken into consideration. For implementing the proposed CLSC model, two conventional approaches and the pro-HGA are used in numerical experiment and their performances are compared with each other using various measures of performance. The experimental results show that the pro-HGA approach is more efficient in locating optimal solution than the other competing approaches.

• IE interfaces
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• v.22 no.2
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• pp.153-164
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• 2009

An effective management for reverse flows of products such as reuse, repair and disposal, has become an important issue for every aspect of business. In this paper, we study the Location-Routing Problem (LRP) in the multi-stage closed-loop supply chain network. The closed-loop supply chain in this study integrated both forward and reverse flows. In forward flow, a factory, Distribution Center (DC) and retailer are considered as usual. Additionally in reverse flow, we consider the Central Returns collection Center (CRC) and disposal facility. We propose a mixed integer programming model for the design of closed-loop supply chain integrating both forward and reverse flows. Since the LRP belongs to an NP-hard problem, we suggest a heuristic algorithm based on genetic algorithm. For some test problems, we found the optimal locations and routes by changing the numbers of retailers and facility candidates. Furthermore, we compare the efficiencies between open-loop and closed-loop supply chain networks. The results show that the closed-loop design is better than the open one in respect to the total routing distance and cost. This phenomenon enlarges the cut down effect on cost as an experimental space become larger.