Abstract
Problem statement: The Capacitated Vehicle Routing Problem (CVRP) is a well-known combinatorial optimization problem which is concerned with the distribution of goods between the depot and customers. It is of economic importance to businesses as approximately 10-20% of the final cost of the goods is contributed by the transportation process. Approach: This problem was tackled using an Ant Colony Optimization (ACO) combined with heuristic approaches that act as the route improvement strategies. The proposed ACO utilized a pheromone evaporation procedure of standard ant algorithm in order to introduce an evaporation rate that depends on the solutions found by the artificial ants. Results: Computational experiments were conducted on benchmark data set and the results obtained from the proposed algorithms shown that the application of combination of two different heuristics in the ACO had the capability to improve the ants’ solutions better than ACO embedded with only one heuristic. Conclusion: ACO with swap and 3-opt heuristic has the capability to tackle the CVRP with satisfactory solution quality and run time. It is a viable alternative for solving the CVRP.
Highlights
The Capacitated Vehicle Routing Problem (CVRP) concerns the design of a set of minimum cost routes, starting and ending at a single depot, for a fleet of vehicles to service a number of customers with known demands
The objective of the CVRP is to find a set of minimum cost routes to serve all the customers by satisfying the following constraints which are listed in Voss (1999): (i) each customer is visited exactly once by exactly one vehicle, (ii) all vehicle routes start and end at the depot, (iii) for each vehicle route, the total demand does not exceed the vehicle capacity Q and (iv) for each vehicle route, the total route length does not exceed a given bound L
This study aims to compare the solution quality of different basic heuristics combined with an original Ant Colony Optimization (ACO) in solving the problem
Summary
The Capacitated Vehicle Routing Problem (CVRP) concerns the design of a set of minimum cost routes, starting and ending at a single depot, for a fleet of vehicles to service a number of customers with known demands It can be represented by a weighted graph G = (V, A) with V = {0,1, 2,..., n} as the vertex set and A = {(i, j) | i, j∈ V} as the edge set. The objective of the CVRP is to find a set of minimum cost routes to serve all the customers by satisfying the following constraints which are listed in Voss (1999): (i) each customer is visited exactly once by exactly one vehicle, (ii) all vehicle routes start and end at the depot, (iii) for each vehicle route, the total demand does not exceed the vehicle capacity Q and (iv) for each vehicle route, the total route length (including service times) does not exceed a given bound L. This study aims to compare the solution quality of different basic heuristics combined with an original ACO in solving the problem
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
