Scheduling a log transport system using simulated annealing

  • Authors:

  • Karunakaran Haridass;Jorge Valenzuela;Ahmet D. Yucekaya;Tim Mcdonald

  • Affiliations:

  • Department of Industrial & Systems Engineering, 3304 Shelby Center, Auburn University, Auburn, AL 36849-5347, USA;Department of Industrial & Systems Engineering, 3304 Shelby Center, Auburn University, Auburn, AL 36849-5347, USA;Department of Industrial Engineering, College of Engineering, Cibali Campus, Kadir Has University, Istanbul, Turkey;Department of Biosystems Engineering, Auburn University, 224 Tom E. Corley Building, Auburn, AL 36849-5347, USA

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2014

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Abstract

The log truck scheduling problem under capacity constraints and time window constraints is an NP-hard problem that involves the design of best possible routes for a set of trucks serving multiple loggers and mills. The objective is to minimize the total unloaded miles traveled by the trucks. In this paper, a simulated annealing - a meta-heuristic optimization method - that interacts with a deterministic simulation model of the log transport system, in which the precedence and temporal relations among activities are explicitly accounted for, is proposed. The results obtained by solving a small size problem consisting of four trucks, two mills, three loggers, and four truck trips showed that the best solution could be found in less than two minutes. In addition, the solution method is tested using data provided by a log delivery trucking firm located in Mississippi. The firm operates sixty-eight trucks to deliver loads from twenty-two logging operations to thirteen mill destinations. The routes assigned by a supervisory person are used as a benchmark to compare the manual generated solution to the solution obtained using the proposed method.