A Neural-Tabu Search Heuristic for the Real Time Vehicle Routing Problem

Jemai, Jaber; Mellouli, Khaled

doi:10.1007/s10852-008-9082-0

Cited by 7 publications

(2 citation statements)

References 39 publications

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“…Several metaheuristic algorithms are also applied to solve VRP problem like Ant Colony Optimization (ACO) as in [35][36][37][38], Tabu Search in [39][40][41][42][43], and Particle Swarm Optimization (PSO) in [44]. Figure 1 summarizes the main three approaches, exact, heuristic, and metaheuristic algorithms, applied in VRP using real-time maps.…”

Section: Metaheuristic Algorithmsmentioning

confidence: 99%

Evaluation of Using Genetic Algorithm and ArcGIS for Determining the Optimal-Time Path in the Optimization of Vehicle Routing Applications

Albalawneh

Mohamed

2022

Mathematical Problems in Engineering

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Transportation is regarded as one of the most important issues currently being researched; this issue needs the search for approaches or processes that might lessen many contemporary traffic concerns. Congestion, pollution, and accidents have escalated lately, negatively impacting urban environments, economic development, and citizens’ lifestyles. The rise of illnesses and epidemics throughout the world, such as COVID-19, has created an urgent need to find the best way to save people’s lives. The vehicle routing problem (VRP) is a well-known moniker for improving transportation systems and is regarded as one of the ancient and contemporary difficulties in route planning applications. One of the main tasks of VRP is serving many customers by determining the optimal route from an initial point to a destination on a real-time road map. The best route is not necessarily the shortest-distance route, but, in emergency cases, it is the route that takes the least fitness cost (time) and the fastest way to arrive. This paper aims to provide an adaptive genetic algorithm (GA) to determine the optimal time route, taking into account the factors that influence the vehicle arrival time and cause delays. In addition, the Network Analyst tool in ArcGIS is used to determine the optimal route using real-time map based on the user’s preferences and suggest the best one. Experimental results indicate that the performance of GA is mainly determined by an efficient representation, evaluation of fitness function, and other factors such as population size and selection method.

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Section: Metaheuristic Algorithmsmentioning

confidence: 99%

Evaluation of Using Genetic Algorithm and ArcGIS for Determining the Optimal-Time Path in the Optimization of Vehicle Routing Applications

Albalawneh

Mohamed

2022

Mathematical Problems in Engineering

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“…Various heuristic methods may be found in literature for VRPTW in [7] and [8]. In this area, Czesh and Czarnas [9] and Chiang and Russell [10] solved VRPTW with simulated annealing, Jemai and Mellouli [11], Taillard et al [12] and Cordeau et al [13] solved VRPTW with tabu search and Gambardella et al [14] applied multiple ant colony system for VRPTW. In addition there are many papers which used genetic algorithm for VRPTW [15][16][17][18][19][20][21][22][23][24][25][26][27].…”

Section: Vehicle Routing Problem With Time Windows (Vrptw)mentioning

confidence: 99%

High-Level Relay Hybrid Metaheuristic Method for Multi-Depot Vehicle Routing Problem with Time Windows

Noori

Ghannadpour

2011

J Math Model Algor

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This paper presents an efficient hybrid metaheuristic solution for multidepot vehicle routing with time windows (MD-VRPTW). MD-VRPTW involves the routing of a set of vehicles with limited capacity from a set of depots to a set of geographically dispersed customers with known demands and predefined time windows. The present work aims at using a hybrid metaheuristic algorithm in the class of High-Level Relay Hybrid (HRH) which works in three levels and uses an efficient genetic algorithm as the main optimization algorithm and tabu search as an improvement method. In the genetic algorithm various heuristics incorporate local exploitation in the evolutionary search. An operator deletion-retrieval strategy is executed which shows the efficiency of the inner working of the proposed method. The proposed algorithm is applied to solve the problems of the standard Cordeau's Instances. Results show that proposed approach is quite effective, as it provides solutions that are competitive with the best known in the literature.

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A multi-objective vehicle routing and scheduling problem with uncertainty in customers’ request and priority

2012

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A Neural-Tabu Search Heuristic for the Real Time Vehicle Routing Problem

Cited by 7 publications

References 39 publications

Evaluation of Using Genetic Algorithm and ArcGIS for Determining the Optimal-Time Path in the Optimization of Vehicle Routing Applications

Evaluation of Using Genetic Algorithm and ArcGIS for Determining the Optimal-Time Path in the Optimization of Vehicle Routing Applications

High-Level Relay Hybrid Metaheuristic Method for Multi-Depot Vehicle Routing Problem with Time Windows

A multi-objective vehicle routing and scheduling problem with uncertainty in customers’ request and priority

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