A hybrid Tabu search – Variable neighborhood descent algorithm for the cumulative capacitated vehicle routing problem with time windows in humanitarian applications

Kyriakakis, Nikolaos A.; Sevastopoulos, Ioannis; Marinaki, Magdalene; Marinakis, Yannis

doi:10.1016/j.cie.2021.107868

Cited by 39 publications

(10 citation statements)

References 39 publications

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“…The ALNS is a single-based metaheuristic extension of the LNS algorithm that use the repair and destroy method with a weight adjusted dynamically during the search of solution. It was read other papers with different solution techniques to solve VRP problems, but they were discarded because weren't related of the VRPD problem of this study, as example the hybrid metaheuristic Tabu Search-Variable Neighborhood Descendent [16] and Greedy Random Adaptive Search Procedure [17].…”

Section: Results Analysismentioning

confidence: 99%

Um modelo conceitual para drones e caminhões cooperativos inteligentes em operação logística

Avelino,

Caetano,

José da Silva

2023

Spectrum

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Drones, também conhecidos como Unmanned Aerial Vehicle (UAV), têm sido considerados o futuro do transporte aéreo para aplicações no contexto de operações logísticas. Eles podem ser usados colaborativamente com caminhões em operações que aproveitam as vantagens de cada um, comumente conhecido como Problema de Roteamento de Veículos com Drones (VRP-D) na perspectiva da pesquisa operacional. Recentemente, têm sido propostos métodos de solução para o VRP-D, porém, há uma vasta oportunidade no desenvolvimento de modelos estruturais. Com isso, esse artigo propõe um modelo conceitual a partir de uma comparação analítica do estado-da-arte em metaheurísticas. O modelo conceitual proposto considera o método exato para pequenas instâncias, já que este garante soluções ótimas, e considera o uso dos métodos heurísticos em instâncias maiores, priorizando-se o balanço entre a qualidade da solução e o tempo computacional. Essa proposta pode ser utilizada nas decisões sobre a melhor abordagem de acordo com o tamanho do problema real, podendo ser aprimorada incorporando-se outros métodos mais recentes, como hibridização e inteligência artificial.

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Section: Results Analysismentioning

confidence: 99%

Um modelo conceitual para drones e caminhões cooperativos inteligentes em operação logística

Avelino,

Caetano,

José da Silva

2023

Spectrum

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“…TS is generally developed for solving combinatorial optimization problems such as the facility location problem [22], the scheduling problem [23], the maximum diversity problem [24], and the vehicle routing problem [25]. TS can also be combined with many algorithms to improve the solution, such as variable neighbourhood descent algorithm [26], evolutionary algorithm [24], genetic algorithm [27], and simulated annealing [28].…”

Section: Tabu Searchmentioning

confidence: 99%

Firefly Algorithm with Tabu Search to Solve the Vehicle Routing Problem with Minimized Fuel Emissions: Case Study of Canned Fruits Transport

Paisarnvirosrak,

Rungrueang

2023

LOGI – Scientific Journal on Transport and Logistics

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Nowadays, logistics is used to assess economic growth and address energy consumption and environmental problems. Optimizing collection and delivery routes reduces fuel consumption and cost, thereby minimizing greenhouse gas (GHG) emissions. The vehicle routing problem with time windows (VRPTW) is addressed to identify routes that minimize total transportation costs, fuel consumption, and GHG emissions based on collection and delivery activities. Firefly Algorithm (FA) integrated with Tabu Search (TS) as (FATS) was proposed within the case study concerning canned fruit transport. The results showed that the proposed method outperformed the existing approaches and reduced the fuel consumption from 31,286 to 26,314 litres per year. The proposed algorithm also reduced the number of used vehicles from seven to six, as five 6-wheel trucks and one 4-wheel truck, with transportation cost reduced from 1,061,851 to 893,108 Baht per year, as well as greenhouse gas emissions, which were reduced from 90,730 to 76,312 kg CO 2 per year.

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“…As the scale of the problem gradually increases, partial literatures proposed using heuristic algorithms to solve VRP. The basic idea of heuristic algorithms is to design heuristic functions to provide a feasible solution to the problem to be solved within an acceptable range [11][12][13][14][15][16]. Compared to the former, when handling large scale VRPs, the heuristic algorithms showcased better feasibility, and can search for the optimal solution of the problem in a short time, which improved vehicle routing's accuracy further.…”

Section: Introductionmentioning

confidence: 99%

Green Vehicle Routing Optimization Based on Dynamic Constraint Selection Co-evolutionary Algorithm

Zhou,

Zhang,

2024

Preprint

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Aiming at the problems of single solution objective in the existing green vehicle routing optimization process and real-time speed change during vehicle travel, a multi-objective green vehicle routing problem with time window constraints in time-varying conditions(MOGVRPTW-TV) is established, then a co-evolutionary framework-based constrained multi-objective evolutionary algorithm for the solving of the model is proposed. First, in order to better match the actual logistics distribution, this model considers the impact of time-varying speed and capacitated variation on carbon emissions based on capacitated constraints and time window constraints. Second, a constrained multi-objective evolutionary algorithm based on the co-evolutionary framework was proposed for model solving. The algorithm treats the complete problem model as a complex task and introduces a shift crowding distance calculation that considers both individual distribution and convergence information when solving this complex task, effectively balancing the convergence and diversity of solutions. Then, a dynamic constraint selection strategy is designed for the implementation of the simple task, which only considers the effects of some constraints on the populations, and the two populations exchange information through offspring populations to achieve overall optimization. Simulations are performed on different instances and the results show that the proposed algorithm is effective in avoiding traffic congestion periods, decreasing overall distribution costs, and reducing fuel consumption and carbon emissions of vehicles.

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A hybrid Tabu search – Variable neighborhood descent algorithm for the cumulative capacitated vehicle routing problem with time windows in humanitarian applications

Cited by 39 publications

References 39 publications

Um modelo conceitual para drones e caminhões cooperativos inteligentes em operação logística

Um modelo conceitual para drones e caminhões cooperativos inteligentes em operação logística

Firefly Algorithm with Tabu Search to Solve the Vehicle Routing Problem with Minimized Fuel Emissions: Case Study of Canned Fruits Transport

Green Vehicle Routing Optimization Based on Dynamic Constraint Selection Co-evolutionary Algorithm

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