Simulation-optimization approach for the stochastic location-routing problem Academic Article

journal

  • Journal of Simulation

abstract

  • The location routing problem with stochastic transportation cost and vehicle travel speeds is considered in this paper. A hybrid solution procedure based on Ant Colony Optimisation (ACO) and Discrete-Event Simulation (DES) is proposed. After using a sequential heuristic algorithm to solve the location subproblem, the subsequent capacitated vehicle routing problem is solved using ACO. Finally, a DES model evaluates those vehicle routes in terms of their impact on the expected total costs. The approach is tested using well-known randomly generated datasets. Since no previous works in the literature studied exactly the same SLRP, the proposed procedure is compared against its deterministic version. Numerical results show the efficiency and efficacy of the hybrid ACO-DES approach.

publication date

  • 2015-11-1

edition

  • 9

keywords

  • Ant Colony Optimization
  • Ant colony optimization
  • Costs
  • Discrete Event Simulation
  • Discrete event simulation
  • Efficacy
  • Evaluate
  • Heuristic Algorithm
  • Heuristic algorithm
  • Heuristic algorithms
  • Hybrid Optimization
  • Location Problem
  • Numerical Results
  • Routing Problem
  • Sequential Algorithm
  • Simulation Model
  • Simulation Optimization
  • Transportation Costs
  • Vehicle Routing Problem
  • Vehicle routing

International Standard Serial Number (ISSN)

  • 1747-7778

number of pages

  • 16

start page

  • 296

end page

  • 311