Solving dial-a-ride problems using multiple ant colony system with fleet size minimisation

Solving dial-a-ride problems using multiple ant colony system with fleet size minimisation

This paper proposes an ant colony optimization (ACO) based algorithm to minimise the fleet size required to solve dial-a-ride problem (DARP). In this work, a static multi-vehicle case of DARP is considered where routes of multiple vehicles are designed to serve customer requests which are known a pr...

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Bibliographic Details
Main Authors: Tripathy, Twinkle, Nagavarapu, Sarat Chandra, Azizian, Kaveh, Pandi, Ramesh Ramasamy, Dauwels, Justin
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2020
Subjects:
Engineering::Electrical and electronic engineering
Dial-a-ride Problem
Fleet Size Minimisation
Online Access:https://hdl.handle.net/10356/140330
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Institution: Nanyang Technological University
Language: English
Description
Summary:This paper proposes an ant colony optimization (ACO) based algorithm to minimise the fleet size required to solve dial-a-ride problem (DARP). In this work, a static multi-vehicle case of DARP is considered where routes of multiple vehicles are designed to serve customer requests which are known a priori. DARP necessitates the need of high quality algorithm to provide optimal feasible solutions. We employ an improved ACO algorithm called ant colony system (ACS) to solve DARP. The fleet minimisation is also achieved by using ACS. In summary, multiple ACS are employed to minimise the fleet size while generating feasible solutions for DARP. Furthermore, the theoretical results are also validated through simulations.

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