scholarly journals Optimization Approach of the Vehicle Routing Problem with Packing Constraints Using Genetic Algorithm

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Nurlita Gamayanti
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Transportation Cost ◽  
Optimization Approach ◽  
Routing Problem ◽  
Final Project ◽  
Loading Method ◽  
Shaped Container ◽  
Packing Process ◽  
Bottom Left

Vehicle Routing Problem is an issue in item delivery from depot to its customers using several vehicles which have limited capacity with a purpose to minimize transportation cost. The packing constraints exist because the vehicles which are usually used in item delivery have rectangular-box shaped container. Also, the items are commonly in shape of rectangular-box. Therefore, packing or loading method is needed so that containers could load all of the items without causing damage and could ease unloading process. The purpose of this final project is to develop a model and algorithm using metaheuristics method, especially genetics algorithm in order to minimize total delivery distance. A hybrid genetics algorithm and bottom-left fill algorithm also take place to solve the packing process. This algorithm delivered average solution 0.08% worse than ant colony optimization, but had 2.93% better solution than tabu search.

A Shuffled Frog Leaping Algorithm for Solving Vehicle Routing Problem

2012 ◽  
Vol 197 ◽  
pp. 529-533 ◽  
Author(s):  
Kai Ping Luo
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
High Efficiency ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Shuffled Frog Leaping Algorithm ◽  
Routing Problem ◽  
Shuffled Frog Leaping ◽  
Encoding Method ◽  
Nearest Neighborhood

For vehicle routing problem, its model is easy to state and difficult to solve. The shuffled frog leaping algorithm is a novel meta-heuristic optimization approach and has strong quickly optimal searching power. The paper applies herein this algorithm to solve the vehicle routing problem; presents a high-efficiency encoding method based on the nearest neighborhood list; improves evolution strategies of the algorithm in order to keep excellent characteristics of the best frog. This proposed algorithm provides a new idea for solving VRP.

scholarly journals A Hybrid Ant Colony Optimization for Dynamic Multidepot Vehicle Routing Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Haitao Xu ◽  
Pan Pu ◽  
Feng Duan
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony ◽  
Optimization Approach ◽  
Dynamic Vehicle Routing ◽  
Routing Problem ◽  
Multiple Depots ◽  
Mutation Operation ◽  
Clustering Approach

In the real world, the vehicle routing problem (VRP) is dynamic and variable, so dynamic vehicle routing problem (DVRP) has obtained more and more attentions among researchers. Meanwhile, due to actual constraints of service hours and service distances, logistics companies usually build multiple depots to serve a great number of dispersed customers. Thus, the research of dynamic multidepot vehicle routing problem (DMDVRP) is significant and essential. However, it has not attracted much attention. In this paper, firstly, a clustering approach based on the nearest distance is proposed to allocate all customers to the depots. Then a hybrid ant colony optimization (HACO) with mutation operation and local interchange is introduced to optimize vehicle routes. In addition, in order to deal with dynamic problem of DMDVRP quickly, a real-time addition and optimization approach is designed to handle the new customer requests. Finally, the t-test is applied to evaluate the proposed algorithm; meanwhile the relations between degrees of dynamism (dod) and HACO are discussed minutely. Experimental results show that the HACO algorithm is feasible and efficient to solve DMDVRP.

scholarly journals Methodology to Solve a Special Case of the Vehicle Routing Problem: A Case Study in the Raw Milk Transportation System

2019 ◽  
Vol 1 (1) ◽  
pp. 75-93 ◽  
Author(s):  
Peerawat Chokanat ◽  
Rapeepan Pitakaso ◽  
Kanchana Sethanan
Keyword(s):  
Differential Evolution ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Differential Evolution Algorithm ◽  
Transportation Cost ◽  
Raw Milk ◽  
Routing Problem ◽  
Trial Vector ◽  
Evolution Algorithm ◽  
Special Case

This research aims to solve the problem of the raw milk collection and transportation system which can be interpreted as a special case of the vehicle routing problem. In the proposed problem, the factory will send the trucks, multiple fleets composed of several compartments, to collect the raw milk from the raw milk farms. The objective of this research is to minimize the total transportation cost and the trucks’ and tanks’ cleaning costs. The transportation cost directly depends on the fuel usage. The fuel usage occurs during the transportation of the milk and during the waiting times when it arrives at the factory and cannot transfer the raw milk into the production tank. We develop the modified differential evolution algorithm (MDE) to solve the proposed problem. The original process of the Differential Evolution algorithm (DE) has been modified in two folds which are as follows: (1) In the recombination process, the 2nd order of trial vectors has been generated using 3 different strategies and compared with the 1st order trial vector; the better from the 1st and the 2nd order of trial vectors will move to the selection process. (2) The probability function has been used to select the new target vector from one of two sources which are the trial vector and the current target vector so that the worse solution can be accepted in order to increase the diversity of the original DE. The computational result shows that the modified DE (MDE) outperforms the original DE in finding a better solution.

TSP based Evolutionary optimization approach for the Vehicle Routing Problem

2009 ◽  
Author(s):  
Zoulel Kouki ◽  
Besma Fayech Chaar ◽  
Mekki Ksouri ◽  
Lotfi Beji ◽  
Samir Otmane ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Evolutionary Optimization ◽  
Optimization Approach ◽  
Routing Problem
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