Location-Routing Optimization of Cold Chain Distribution Center Based on Hybrid Genetic Algorithm - Tabu Search

Author(s):  
Guohua Zheng ◽  
Liangxia Liu ◽  
Lichao Deng
2020 ◽  
Vol 10 (7) ◽  
pp. 2564
Author(s):  
Liying Yan ◽  
Manel Grifoll ◽  
Pengjun Zheng

Taking cold-chain logistics as the research background and combining with the overall optimisation of logistics distribution networks, we develop two-stage distribution location-routing model with the minimum total cost as the objective function and varying vehicle capacity in different delivery stages. A hybrid genetic algorithm is designed based on coupling and collaboration of the two-stage routing and transfer stations. The validity and feasibility of the model and algorithm are verified by conducting a randomly generated test. The optimal solutions for different objective functions of two-stage distribution location-routing are compared and analysed. Results turn out that for different distribution objectives, different distribution schemes should be employed. Finally, we compare the two-stage distribution location-routing to single-stage vehicle routing problems. It is found that a two-stage distribution location-routing system is feasible and effective for the cold-chain logistics network, and can decrease distribution cost for cold-chain logistics enterprises.


2017 ◽  
Vol 10 (5) ◽  
pp. 853
Author(s):  
Narong Wichapa ◽  
Porntep Khokhajaikiat

Purpose: Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management.Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move.Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively.Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.


2019 ◽  
Vol 53 (6) ◽  
pp. 572-572
Author(s):  
Liyi Zhang ◽  
Yang Gao ◽  
Yunshan Sun ◽  
Teng Fei ◽  
Yujing Wang

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