A genetic algorithm based task scheduling system for logistics service robots

Sariffuddin Harun, Mohd Faisal Ibrahim

Research output: Contribution to journalArticle

Abstract

The demand for autonomous logistics service robots requires an efficient task scheduling system in order to optimise cost and time for the robot to complete its tasks. This paper presents a Genetic algorithm (GA) based task scheduling system for a ground mobile robot that is able to find a global near-optimal travelling path to complete a logistics task of pick-and-deliver items at various locations. In this study, the chromosome representation and the fitness function of GA is carefully designed to cater for a single load logistics robotic task. Two variants of GA crossover are adopted to enhance the performance of the proposed algorithm. The performance of the scheduling is compared and analysed between the proposed GA algorithms and a conventional greedy algorithm in a virtual map and a real map environments that turns out the proposed GA algorithms outperform the greedy algorithm by 40% to 80% improvement.

Original languageEnglish
Pages (from-to)206-213
Number of pages8
JournalBulletin of Electrical Engineering and Informatics
Volume8
Issue number1
DOIs
Publication statusPublished - 1 Mar 2019

Fingerprint

Service Robot
Task Scheduling
scheduling
logistics
robots
genetic algorithms
Logistics
Genetic algorithms
Scheduling
Genetic Algorithm
Robots
greedy algorithms
Greedy Algorithm
fitness
chromosomes
Chromosomes
Fitness Function
robotics
Mobile Robot
Mobile robots

Keywords

  • Autonomous robot
  • Genetic algorithm
  • Logistics service robot
  • Robotic task scheduling

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Hardware and Architecture
  • Computer Networks and Communications
  • Control and Optimization
  • Electrical and Electronic Engineering

Cite this

A genetic algorithm based task scheduling system for logistics service robots. / Harun, Sariffuddin; Ibrahim, Mohd Faisal.

In: Bulletin of Electrical Engineering and Informatics, Vol. 8, No. 1, 01.03.2019, p. 206-213.

Research output: Contribution to journalArticle

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