Clustering-Locating-Routing Algorithm for Vehicle Routing Problem: An Application in Medical Equipment Maintenance

Author(s):  
Kanokwan Supakdee ◽  
Natthapong Nanthasamroeng ◽  
Rapeepan Pitakaso
Author(s):  
A.K. Pamosoaji ◽  
P.K. Dewa ◽  
J.V. Krisnanta

A multi-objective distribution routing algorithm by using modified Clarke and Wright Saving algorithm is presented. The problem to solve is to deliver loads to a number of outlets based load requirement. The objective function to minimize is the distance saving and traveling time of the resulted route started from depot to the outlets and return to the original depot. Problem to solve is generating a distribution route in a week considering traffic condition for each day. The original Clarke and Wright saving algorithm is modified such that the resulted routes (from a depot to some outlets) accommodates some constraints such as the maximum allowable traveling time, maximum number of delivery shifts, and maximum number of vehicles. The algorithm is applied to a distributor company with nine outlets, two vehicles, and two delivery shifts. In addition, the traffic condition on the outlet-to-outlet and the depot-to-outlet routes is considered. The simulation of the proposed algorithm shows that the algorithm can generate routes that comply with shift’s maximum delivery time and the vehicles’ capacities. 


2020 ◽  
Vol 23 ◽  
pp. 55-63
Author(s):  
Hanne Pollaris ◽  
Gerrit Karel Janssens ◽  
Kris Braekers ◽  
An Caris

A vehicle routing problem (VRP) with sequence-based pallet loading and axle weight constraints is introduced in the study. An Iterated Local Search (ILS) metaheuristic algorithm is used to solve the problem. Like any metaheuristic, a number of parameters need to be set before running the experiments. Parameter tuning is important because the value of the parameters may have a substantial impact on the efficacy of a heuristic algorithm. While traditionally, parameter values have been set manually using expertise and experimentation, recently several automated tuning methods have been proposed. The performance of the routing algorithm is mostly improved by using parameter tuning, but no single best tuning method for routing algorithms exists. The tuning method, Iterated F-race, is chosen because it seems to be a very robust method and it has been shown to perform well on the ILS metaheuristic and other metaheuristics. The research aims at developing an algorithm, which performs well over a wide range of network sizes.


Sign in / Sign up

Export Citation Format

Share Document