An adaptive large neighborhood search heuristic for the cumulative capacitated vehicle routing problem

Ribeiro, Glaydston Mattos; Laporte, Gilbert

doi:10.1016/j.cor.2011.05.005

Cited by 221 publications

(38 citation statements)

References 20 publications

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“…This is due to the practical application of these problems in real life: for example, in transportation and industrial manufacturing. Some recent examples of these works are [15,16]. In this kind of studies, with the aim of exploiting and exploring the solution space more exhaustively, heuristic functions are used.…”

Section: Introductionmentioning

confidence: 99%

On the influence of using initialization functions on genetic algorithms solving combinatorial optimization problems: A first study on the TSP

Osaba

Carballedo

Díaz

et al. 2014

2014 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)

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Combinatorial optimization is a widely studied field within artificial intelligence. There are many problems of this type, and many techniques applied to them can be found in the literature. Especially, population techniques have received much attention in this area, being genetic algorithms (GA) the most famous ones. Although throughout history many studies on GAs have been performed, there is still no study like the presented in this work. In this paper, a study on the influence of using heuristic initialization functions in genetic algorithms (GA) applied to combinatorial optimization problems is performed. Being the first phase of this research, the study is conducted using one of the best known problems in combinatorial optimization: the traveling salesman problem. Three different experimentations are carried out, using three different heuristic initialization functions. Additionally, for each experiment four versions of a GA have been developed for the comparison. Each of these variant differs in the initialization phase. The results obtained by each GA are compared to determine the influence of the use of heuristic functions for the initialization of the population.

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Section: Introductionmentioning

confidence: 99%

On the influence of using initialization functions on genetic algorithms solving combinatorial optimization problems: A first study on the TSP

Osaba

Carballedo

Díaz

et al. 2014

2014 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)

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“… Previous LNS implementations have made use of other metaheuristic algorithms at the master level to guide the search to new regions and accept improved solutions such as Simulated Annealing (Mattos Ribeiro & Laporte, 2012;Ropke & Pisinger, 2006). In the neighbourhood exploration, applying noise in recreation procedures also avoids stagnation e.g., by using randomisation in the insertion evaluation function in recreation procedures (Ropke & Pisinger, 2006), or tailoring recreation procedures to ensure diversification (Mattos Ribeiro & Laporte, 2012).…”

Section: Large Neighbourhood Searchmentioning

confidence: 99%

“…In the case of the TDVRPTW, any solution with unscheduled customers is infeasible. Additionally, insertion procedures are quite myopic, in order to avoid stagnating search processes, where destruction and recreation procedures keep performing the same modification to a solution, providing diversification in different levels of the search process might improve accuracy of solutions (Mattos Ribeiro & Laporte, 2012).…”

Section: Large Neighbourhood Searchmentioning

confidence: 99%

A hybrid metaheuristic for the time-dependent vehicle routing problem with hard time windows

Rincón-García¹,

Waterson²,

Cherrett³

2017

10.5267/j.ijiec

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This article paper presents a hybrid metaheuristic algorithm to solve the time-dependent vehicle routing problem with hard time windows. Time-dependent travel times are influenced by different congestion levels experienced throughout the day. Vehicle scheduling without consideration of congestion might lead to underestimation of travel times and consequently missed deliveries. The algorithm presented in this paper makes use of Large Neighbourhood Search approaches and Variable Neighbourhood Search techniques to guide the search. A first stage is specifically designed to reduce the number of vehicles required in a search space by the reduction of penalties generated by time-window violations with Large Neighbourhood Search procedures. A second stage minimises the travel distance and travel time in an 'always feasible' search space. Comparison of results with available test instances shows that the proposed algorithm is capable of obtaining a reduction in the number of vehicles (4.15%), travel distance (10.88%) and travel time (12.00%) compared to previous implementations in reasonable time.

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“…Emec et al [37] presented new removal, insertion, and vendor selection allocation mechanisms. Ribeiro and Laporte [38] proposed an ALNS for solving the cumulative capacitated vehicle routing problem (CCVRP). Hemmelmayr et al [39] proposed an ALNS heuristic for the two-echelon vehicle routing problem (2E-VRP).…”

Section: Introductionmentioning

confidence: 99%

Heuristics Algorithms for a Heterogeneous Fleets VRP with Excessive Demand for the Vehicle at the Pickup Points, and the Longest Traveling Time Constraint: A Case Study in Prasitsuksa Songkloe, Ubonratchathani Thailand

Kaewman

Akararungruangkul

2018

Logistics

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This paper presents a methodology to solve a special case of the vehicle routing problem (VRP) called the heterogeneous fleets VRP with excessive demand of the vehicle at the pickup points, and the longest time constraint (HFVRP-EXDE-LTC). We developed two metaheuristics-a differential evolution (DE) algorithm and an adaptive large neighborhood search (ALNS)-to solve the problem. These two proposed methods have been designed to effectively solve a special case of VRP. From the computational results, we can see that the proposed heuristics outperformed the best practices that are currently in use. The DE yielded a 9.78% lower cost than that of the current practice (757,250 baht per year), while ALNS generated a 10.89% (906,750 baht per year) lower cost than that of current practice. Comparing the proposed heuristics, ALNS achieved a 1.01% lower cost than that of DE, as ALNS had a better mechanism that was designed to escape from the local optimal.

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An adaptive large neighborhood search heuristic for the cumulative capacitated vehicle routing problem

Cited by 221 publications

References 20 publications

On the influence of using initialization functions on genetic algorithms solving combinatorial optimization problems: A first study on the TSP

On the influence of using initialization functions on genetic algorithms solving combinatorial optimization problems: A first study on the TSP

A hybrid metaheuristic for the time-dependent vehicle routing problem with hard time windows

Heuristics Algorithms for a Heterogeneous Fleets VRP with Excessive Demand for the Vehicle at the Pickup Points, and the Longest Traveling Time Constraint: A Case Study in Prasitsuksa Songkloe, Ubonratchathani Thailand

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