An Artificial Bee Colony Algorithm for Static and Dynamic Capacitated Arc Routing Problems

Abstract

The Capacitated Arc Routing Problem (CARP) is a combinatorial optimization problem, which requires the identification of such route plans on a given graph to a number of vehicles that generates the least total cost. The Dynamic CARP (DCARP) is a variation of the CARP that considers dynamic changes in the problem. The Artificial Bee Colony (ABC) algorithm is an evolutionary optimization algorithm that was proven to be able to provide better performance than many other evolutionary algorithms, but it was not used for the CARP before. For this reason, in this study, an ABC algorithm for the CARP (CARP-ABC) was developed along with a new move operator for the CARP, the sub-route plan operator. The CARP-ABC algorithm was tested both as a CARP and a DCARP solver, then its performance was compared with other existing algorithms. The results showed that it excels in finding a relatively good quality solution in a short amount of time, which makes it a competitive solution. The efficiency of the sub-route plan operator was also tested and the results showed that it is more likely to find better solutions than other operators.

ABC-ANN Based Indoor Position Estimation Using Preprocessed RSSI

“…Complexity analysis of the ABC optimization algorithm has been done in many studies. Nagy et al reported the ABC algorithm as O(n + log n) in their study [42]. Since the ABC algorithm used is the classical ABC algorithm, the complexity value presented in previous studies is also valid here.…”

Low-Carbon Routing Based on Improved Artificial Bee Colony Algorithm for Electric Trackless Rubber-Tyred Vehicles

“…With the development of intelligence optimization methods, variable neighborhood search [17] , genetic algorithm [18] , ant colony optimization [19] , and artificial bee colony algorithm (ABC) [20] have been employed to achieve the optimal routing scheme within acceptable computational time. Among them, artificial bee colony algorithm inspired by bee colony behavior has simpler structure with few parameters and thus has been widely applied in solving combinatorial optimization problems, such as traveling salesman problem [21] , arc routing problem [22] , and vehicle routing problem [23,24] . Although many problem-specific operators have been designed to enhance the ability of exploration and exploitation for ABC, their limitations will be exposed on solving other problems due to no free lunch theorems [25] .…”