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Real Time Vehicle Routing Problem with Time Window Simultaneously Delivery Products and Pick up Wastage Materials with Proposed Master-Slave Genetic Algorithm

by Padmabati Chand, J. R. Mohanty
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 19
Year of Publication: 2013
Authors: Padmabati Chand, J. R. Mohanty
10.5120/12653-9359

Padmabati Chand, J. R. Mohanty . Real Time Vehicle Routing Problem with Time Window Simultaneously Delivery Products and Pick up Wastage Materials with Proposed Master-Slave Genetic Algorithm. International Journal of Computer Applications. 72, 19 ( June 2013), 39-46. DOI=10.5120/12653-9359

@article{ 10.5120/12653-9359,
author = { Padmabati Chand, J. R. Mohanty },
title = { Real Time Vehicle Routing Problem with Time Window Simultaneously Delivery Products and Pick up Wastage Materials with Proposed Master-Slave Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 19 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 39-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number19/12653-9359/ },
doi = { 10.5120/12653-9359 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:38:22.614858+05:30
%A Padmabati Chand
%A J. R. Mohanty
%T Real Time Vehicle Routing Problem with Time Window Simultaneously Delivery Products and Pick up Wastage Materials with Proposed Master-Slave Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 19
%P 39-46
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The real-time vehicle routing problem with time windows and simultaneous delivery products and pickup wastage materials (RT-VRPTWDPPWM) is formulated as extension of VRP. The real-time delivery/pickup demands are served by capacitated vehicles with limited initial loads. Moreover, pickup services aren't necessarily done after delivery services in each route. A improved genetic algorithm ( master-slave genetic algorithm)is proposed. To generate offspring for the next generation for crossover (Sub Route Sequence Crossover Method (SRSCM) and for mutation (Sub Route Alter Mutation Method (SRAMM) methods are introduced. The results shows that the proposed algorithm can efficiently decrease the total route cost. Results of comparative tests are presented showing that the improved algorithm performs well on large populations.

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Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm (GA) Multi Objective Genetic Algorithm (MOGA) Sub Route Sequence Crossover Method (SRSCM) Sub Route Alter Mutation Method (SRAMM) Vehicle Routing Problem (VRP)

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