Redesign of the supply of mobile mechanics based on a novel genetic optimization algorithm using Google Maps API

András Király, J. Abonyi

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

If a mobile mechanic has to travel for material, productive time is lost. This paper presents a novel method to reduce activities regarding material handling with extending of serving locations. The design of the supply system can be considered as a complex combinatorial optimization problem, where the goal is to find a route plan with minimal route cost, which services all the demands from the central warehouses while satisfying the capacity and other constraints. We present a multi-chromosome technique for solving the multiple Traveling Salesman Problem (mTSP). The new operators based on a problem-specific representation proved to be more effective in terms of flexibility, complexity and transparency, and also in efficiency than the previous methods. The proposed optimization algorithm was implemented in MATLAB and integrated with Google Maps to provide a complete framework for distance calculation, definition of the initial routes, and visualization. This integrated framework was successfully applied in the solution of a real logistic problem, in the supply of mobile mechanics at one of Hungarys biggest energy providers.

Original languageEnglish
Pages (from-to)122-130
Number of pages9
JournalEngineering Applications of Artificial Intelligence
Volume38
DOIs
Publication statusPublished - Feb 1 2015

Fingerprint

Application programming interfaces (API)
Mechanics
Traveling salesman problem
Warehouses
Combinatorial optimization
Materials handling
Chromosomes
Transparency
MATLAB
Mathematical operators
Logistics
Visualization
Costs

Keywords

  • Genetic algorithm
  • Genetic representation
  • Google Maps
  • mTSP
  • Optimization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

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