scholarly journals Profit maximization in reverse logistics based on disassembly scheduling using hybrid bee colony and bat optimization

2019 ◽  
Vol 43 (4) ◽  
pp. 551-559 ◽  
Author(s):  
T. Sathish
Keyword(s):  
End Of Life ◽  
Reverse Logistics ◽  
Optimization Technique ◽  
Profit Maximization ◽  
Manufacturing Industries ◽  
Bee Colony ◽  
Reverse Logistic ◽  
Novel Strategy ◽  
Suitable Technique

This work was undertaken to develop a strategy to enhance the profit in the reverse logistics of end-of-life products. In this paper, a novel strategy based on hybrid bee colony and bat optimization technique is presented to perform reverse logistics. The aim of the present paper is to maximize the profit in reverse logistic based manufacturing. The proposed optimization technique was used to schedule the disassembly of end-of-life products so that the time spent in reverse logistics was reduced. Moreover, the proposed technique increases the amount of product required during disassembly, so that the loss of component is reduced. Thus, the proposed technique can enhance the manufacturer’s profit by reducing the time and cost required for disassembly. Ultimately, the proposed technique can provide a suitable technique for multi-period disassembly in manufacturing industries.

Reverse Logistics Network Design for the Collection of End-of-Life Vehicles

2012 ◽  
Author(s):  
Hang Dai ◽  
Qing Wang
Keyword(s):  
Network Design ◽  
End Of Life ◽  
Facility Location ◽  
Reverse Logistics ◽  
Location Problem ◽  
Strategic Decision ◽  
Mixed Integer ◽  
Logistics Network ◽  
Reverse Logistics Network ◽  
Reverse Logistic

Reverse logistic network design problems involve strategic decisions which influence tactical and operational decisions. In particular, they involve facility location, transportation and inventory decisions, which affect the cost of the distribution system and the quality of the customer service level. Locating a collection centre is an important strategic decision, as purchasing or building facilities requires sizable investment; also the network transportation cost is affected by the selection of facility locations. The location that is selected must therefore take into account all the parameters and variables that are relevant and the decision may even affect demand. In this paper, network design for reverse logistics is investigated to solve the End-of-life Vehicles (ELV) collection centres location problem. We start by giving an understanding of the process of this reverse logistics network design by considering the features of reverse logistics, the role of ELV management and use of optimization methods. Based on this, a reverse logistics network design case for collection of End-of-life Vehicles is presented by formulating the problem into a mixed-integer linear program (MILP), taking into consideration the Capacitated Facility Location Problem. The solution to this model is obtained using IBM CPLEX Optimization Studio©. In addition the applicability of the model in other reverse logistic networks is discussed and the subjects for further research are pointed out.

scholarly journals Sustainable reverse logistic network design for End-of-Life Use-Case Study

2019 ◽  
Author(s):  
SUNA CINAR
Keyword(s):  
End Of Life ◽  
Carbon Emissions ◽  
Reverse Logistics ◽  
Practical Implication ◽  
Operating Cost ◽  
Mixed Integer ◽  
Logistics System ◽  
Reverse Logistic ◽  
The Impact

Due to the increased interests in environmental issues along with stringent environmental legislation and regulations, companies start taking a fresh look at the impact on their reverse logistic activties on the environment. This paper is an example of the recovery of valuable material that can be recycled/recovered or remanufactured at the end of product useful life by designing an effective reverse logistics network. In this study, a mixed integer linear programming (MILP) model is proposed to determine a long-term strategy for end-of-life (EOL). The mathematical model not only takes into account the minimization of system operating costs, but also considered minimization of carbon emissions related to the transportation and processing of used products. Therefore, the objective in this model was to minimize the transportation and operating cost as well as minimizing environmental effects these activities. The results of this study show the trade-off between the costs and carbon emissions, and cost effectiveness for improving environmental performance, all of which have great practical implication on decision-making of network configurations a reverse logistics system. The proposed model is validated by examining a case study from wind turbine (WT) sector.

scholarly journals A Hesitant Fuzzy Combined Compromise Solution Framework-Based on Discrimination Measure for Ranking Sustainable Third-Party Reverse Logistic Providers

2021 ◽  
Vol 13 (4) ◽  
pp. 2064
Author(s):  
Arunodaya Raj Mishra ◽  
Pratibha Rani ◽  
Raghunathan Krishankumar ◽  
Edmundas Kazimieras Zavadskas ◽  
Fausto Cavallaro ◽  
...  
Keyword(s):  
Reverse Logistics ◽  
Hybrid Approach ◽  
Third Party ◽  
Illustrative Case ◽  
Primary Concern ◽  
Compromise Solution ◽  
Fuzzy Environment ◽  
Criteria Weights ◽  
Reverse Logistic ◽  
Illustrative Case Study

Customers’ pressure, social responsibility, and government regulations have motivated the enterprises to consider the reverse logistics (RL) in their operations. Recently, companies frequently outsource their RL practices to third-party reverse logistics providers (3PRLPs) to concentrate on their primary concern and diminish costs. However, to select the suitable 3PRLP candidate requires a multi-criteria decision making (MCDM) process involving uncertainty owing to the presence of many associated aspects. In order to choose the most appropriate sustainable 3PRLP (S3PRLP), we introduce a hybrid approach based on the classical Combined Compromise Solution (CoCoSo) method and propose a discrimination measure within the context of hesitant fuzzy sets (HFSs). This approach offers a new process based on the discrimination measure for evaluating the criteria weights. The efficiency and practicability of the present approach are numerically demonstrated by solving an illustrative case study of S3PRLPs selection under a hesitant fuzzy environment. Moreover, sensitivity and comparative studies are presented to highlight the robustness and strength of the introduced methodology. The result of this work concludes that the introduced methodology can recommend a more feasible performance when facing with determinate and inconsistent knowledge and qualitative data.

Mining of structural motifs in proteins using artificial bee colony optimization framework for druggability

2021 ◽  
Author(s):  
L. S. Suma ◽  
S. S. Vinod Chandra
Keyword(s):  
Artificial Bee Colony ◽  
Area Under The Curve ◽  
Docking Studies ◽  
Artificial Bee Colony Optimization ◽  
Optimization Framework ◽  
Bee Colony ◽  
Novel Variant ◽  
Bee Colony Optimization ◽  
Novel Strategy ◽  
Sensitivity Specificity

In this work, we have developed an optimization framework for digging out common structural patterns inherent in DNA binding proteins. A novel variant of the artificial bee colony optimization algorithm is proposed to improve the exploitation process. Experiments on four benchmark objective functions for different dimensions proved the speedier convergence of the algorithm. Also, it has generated optimum features of Helix Turn Helix structural pattern based on the objective function defined with occurrence count on secondary structure. The proposed algorithm outperformed the compared methods in convergence speed and the quality of generated motif features. The motif locations obtained using the derived common pattern are compared with the results of two other motif detection tools. 92% of tested proteins have produced matching locations with the results of the compared methods. The performance of the approach was analyzed with various measures and observed higher sensitivity, specificity and area under the curve values. A novel strategy for druggability finding by docking studies, targeting the motif locations is also discussed.

scholarly journals Reverse Logistics: End-of-Life Recovery Pledge

10.5772/9898 ◽  
2010 ◽  
Author(s):  
Rinaldo Michelini ◽  
Roberto Razzoli
Keyword(s):  
End Of Life ◽  
Reverse Logistics

scholarly journals MODIFIKASI BARU ALGORITMA KOLONI LEBAH BUATAN UNTUK MASALAH OPTIMASI GLOBAL

2018 ◽  
Vol 10 (1) ◽  
pp. 17
Author(s):  
Nursyiva Irsalinda ◽  
Sugiyarto Surono
Keyword(s):  
Food Source ◽  
Artificial Bee Colony ◽  
Selection Process ◽  
Optimization Technique ◽  
Food Sources ◽  
Abc Algorithm ◽  
Average Value ◽  
Bee Colony ◽  
Objective Function Values ◽  
Better Than

Artificial Bee Colony (ABC) algorithm is one of metaheuristic optimization technique based on population. This algorithm mimicking honey bee swarm to find the best food source. ABC algorithm consist of four phases: initialization phase, employed bee phase, onlooker bee phase and scout bee phase. This study modify the onlooker bee phase in selection process to find the neighborhood food source. Not all food sources obtained are randomly sought the neighborhood as in ABC algorithm. Food sources are selected by comparing their objective function values. The food sources that have value lower than average value in that iteration will be chosen by onlooker bee to get the better food source. In this study the modification of this algorithm is called New Modification of Artificial Bee Colony Algorithm (MB-ABC). MB-ABC was applied to 4 Benchmark functions. The results show that MB-ABC algorithm better than ABC algorithm

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