scholarly journals A Hybrid Bat Algorithm with Path Relinking for Capacitated Vehicle Routing Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yongquan Zhou ◽  
Jian Xie ◽  
Hongqing Zheng
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Single Point ◽  
Bat Algorithm ◽  
Theoretical Background ◽  
Path Relinking ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Np Hard Problem ◽  
Capacitated Vehicle

The capacitated vehicle routing problem (CVRP) is an NP-hard problem with wide engineering and theoretical background. In this paper, a hybrid bat algorithm with path relinking (HBA-PR) is proposed to solve CVRP. The HBA-PR is constructed based on the framework of continuous bat algorithm; the greedy randomized adaptive search procedure (GRASP) and path relinking are effectively integrated into bat algorithm. Moreover, in order to further improve the performance, the random subsequences and single-point local search are operated with certain loudness (probability). In order to verify the validity of the method in this paper, and it's efficiency and with other existing methods, several classical CVRP instances from three classes of CVRP benchmarks are selected to tested. Experimental results and comparisons show that the HBA-PR is effective for CVRP.

scholarly journals Implementation of discrete particle swarm optimization algorithm in the capacitated vehicle routing problem

2020 ◽  
Vol 4 (2) ◽  
pp. 117-128
Author(s):  
Aisyahna Nurul Mauliddina ◽  
Faris Ahmad Saifuddin ◽  
Adesatya Lentera Nagari ◽  
Anak Agung Ngurah Perwira Redi ◽  
Adji Candra Kurniawan ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Optimal Solution ◽  
Computational Time ◽  
Hard Problem ◽  
Np Hard ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Np Hard Problem ◽  
Capacitated Vehicle

Capacitated Vehicle Routing Problem (CVRP) is known as an NP-hard problem. It is because CVRP problems are very hard for finding optimal solutions, especially in large instances. In general, the NP-hard problem is difficult to solve in the exact method, so the metaheuristic approach is implemented in the CVRP problem to find a near-optimal solution in reasonable computational time. This research uses the DPSO algorithm for solving CVRP with ten instances of benchmark datasets. DPSO implementation uses tuning parameters with the One Factor at Time (OFAT) method to select the best DPSO parameters. The outcome objective function will be compared with several PSO models proposed in previous studies. Statistical test using One Way Reputed Measure ANOVA is needed to compare algorithm performance. First, ANOVA uses for comparing’s results. Then, ANOVA is also used to test DPSO’s performance compared with DPSO-SA, SR-1, and SR-2 algorithm. The computational result shows that the basic DPSO algorithm not competitive enough with other methods for solving CVRP.

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