An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup

Authors:
Yuvraj Gajpal;Prakash Abad
Affiliations:
Michael G DeGroote School of Business, McMaster University, Hamilton, Ontario, Canada L8S4M4;Michael G DeGroote School of Business, McMaster University, Hamilton, Ontario, Canada L8S4M4
Venue:
Computers and Operations Research
Year:
2009

Citing 11
Cited 11

Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem

Annals of Operations Research - Special issue on Tabu search
Vehicle routing with pick-up and delivery: tour-partitioning heuristics

Computers and Industrial Engineering
MAX-MIN Ant system

Future Generation Computer Systems
SavingsAnts for the Vehicle Routing Problem

Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Performance of Various Computers Using Standard Linear Equations Software

Performance of Various Computers Using Standard Linear Equations Software
D-Ants: savings based ants divide and conquer the vehicle routing problem

Computers and Operations Research
Ant Colony Optimization

Ant Colony Optimization
An ant system algorithm for the mixed vehicle routing problem with backhauls

Metaheuristics
A tabu search algorithm for the vehicle routing problem with simultaneous pick-up and delivery service

Computers and Operations Research
A Branch-and-Price Approach to the Vehicle Routing Problem with Simultaneous Distribution and Collection

Transportation Science
Ant system: optimization by a colony of cooperating agents

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

A parallel heuristic for the Vehicle Routing Problem with Simultaneous Pickup and Delivery

Computers and Operations Research
Multi-route railroad blocking problem by improved model and ant colony algorithm in real world

Computers and Industrial Engineering
An ant colony optimization approach to solve cooperative transportation planning problems

Winter Simulation Conference
Ant colony algorithm for traffic signal timing optimization

Advances in Engineering Software
Scatter search for the stochastic travel-time vehicle routing problem with simultaneous pick-ups and deliveries

Computers and Operations Research
A genetic algorithm based approach to vehicle routing problem with simultaneous pick-up and deliveries

Computers and Industrial Engineering
Software framework for vehicle routing problem with hybrid metaheuristic algorithms

ACC'11/MMACTEE'11 Proceedings of the 13th IASME/WSEAS international conference on Mathematical Methods and Computational Techniques in Electrical Engineering conference on Applied Computing
A two-pheromone trail ant colony system--tabu search approach for the heterogeneous vehicle routing problem with time windows and multiple products

Journal of Heuristics
A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery

Computers and Industrial Engineering
Metaheuristic Approaches for Vehicle Routing Problems

International Journal of Information Systems and Supply Chain Management
A Genetic Algorithm-based optimization model for supporting green transportation operations

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper we use an ant colony system (ACS) algorithm to solve the vehicle routing problem with simultaneous delivery and pickup (VRPSDP) which is a combinatorial optimization problem. ACS is an algorithmic approach inspired by the foraging behavior of real ants. Artificial ants are used to construct a solution for the problem by using the pheromone information from previously generated solutions. The proposed ACS algorithm uses a construction rule as well as two multi-route local search schemes. The algorithm can also solve the vehicle routing problem with backhaul and mixed load (VRPBM). An extensive numerical experiment is performed on benchmark problem instances available in literature. It is found that ACS gives good results compared to the existing algorithms.