Multi-Objective Scheduling of Single Mobile Robot Based on Grey Wolf Optimization Algorithm

29 Pages Posted: 15 Mar 2022

See all articles by Milica Petrović

Milica Petrović

affiliation not provided to SSRN

Aleksandar Jokić

affiliation not provided to SSRN

Zoran Miljković

University of Belgrade - Faculty of Mechanical Engineering

Zbigniew Kulesza

affiliation not provided to SSRN

Abstract

During the last decades, intelligent mobile robots have been recognized as one of the most promising and emerging solutions used to fulfill material transport demands in intelligent manufacturing systems. One of the most significant characteristics of those demands is their multi-objectivity, where identified objectives might usually be in conflict. Therefore, obtaining the optimally scheduled robotic-based material transport system that is simultaneously faced with several conflicting objectives is a highly challenging task. In order to address such a challenge, this paper proposes a novel multi-objective Grey Wolf Optimizer (MOGWO) methodology to efficiently schedule material transport systems based on an intelligent single mobile robot. The proposed optimization methodology includes the comprehensive analysis and the mathematical formulation for 13 novel fitness functions, which are combined to form a Pareto front of the multi-objective optimization problem, as well as a novel strategy for optimal exploration of multi-objective search space. Moreover, four metrics, i.e., Generational Distance (GD), Inverted Generational Distance (IGD), Spacing (SP), and Maximum Spread (MS), are employed to quantitively evaluate and compare the effectiveness of the proposed enhanced MOGWO algorithm with two state-of-the-art metaheuristic methods (MOGA, MOAOA) on 25 benchmark problems. The obtained results achieved through two experimental scenarios indicate that the enhanced MOGWO algorithm outperforms other algorithms in terms of convergence, coverage, and robust optimal Pareto solution obtained. Finally, transportation paths based on obtained scheduling plans are experimentally validated by mobile robot RAICO (Robot with Artificial Intelligence based Cognition) within a physical model of the intelligent manufacturing environment. The achieved experimental results successfully demonstrate the efficiency of the proposed methodology for optimal multi-objective scheduling of material transport tasks based on a single mobile robotic system.

Keywords: multi-objective optimization, Scheduling of robotic systems, Population-based metaheuristics, Grey wolf optimization algorithm, Intelligent manufacturing systems

Suggested Citation

Petrović, Milica and Jokić, Aleksandar and Miljković, Zoran and Kulesza, Zbigniew, Multi-Objective Scheduling of Single Mobile Robot Based on Grey Wolf Optimization Algorithm. Available at SSRN: https://ssrn.com/abstract=4058009 or http://dx.doi.org/10.2139/ssrn.4058009

Milica Petrović (Contact Author)

affiliation not provided to SSRN ( email )

No Address Available

Aleksandar Jokić

affiliation not provided to SSRN ( email )

No Address Available

Zoran Miljković

University of Belgrade - Faculty of Mechanical Engineering ( email )

Studentski trg 1
Belgrade, 11000
Serbia

HOME PAGE: http://www.mas.bg.ac.rs/fakultet/nastavnici/118

Zbigniew Kulesza

affiliation not provided to SSRN ( email )

No Address Available

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