• DocumentCode
    2839561
  • Title

    Scheduling Supply Vessels for An Industrial Oil Exploration Operation: A Multi-Objective Evolutionary Approach

  • Author

    Korgaokar, Surendu ; Mitra, Kishalay

  • Author_Institution
    Tata Consultancy Services Ltd., Pune
  • fYear
    2006
  • fDate
    15-17 Dec. 2006
  • Firstpage
    3038
  • Lastpage
    3043
  • Abstract
    Vessel scheduling for an industrial crude oil exploration operation, coming under the category of vehicle routing problem (VRP), is solved under multiobjective optimization framework. Objectives under consideration are minimization of total time, vessel unutilization and missed demand. Two bi-objective and one triple-objective problems are solved (as per requirement of the industry) and Pareto optimal (PO) solutions are generated for all of them. The demands to be supplied at various installations by splitting across the various heterogeneous vessels are considered as the decision variables. Pareto archived evolutionary strategy (PAES), one of the state-of-the-art evolutionary multi-objective optimization (EMO) algorithms, is chosen for this task. The conventional method based on epsiv-constraints, when used to solve one of the three optimization problems mentioned above, is observed to be completely outperformed by PAES in terms of computation time and resources required to solve the problem.
  • Keywords
    evolutionary computation; petroleum industry; scheduling; transportation; Pareto archived evolutionary strategy; Pareto optimal solutions; industrial oil exploration; multiobjective evolutionary approach; supply vessels scheduling; vehicle routing problem; Computational modeling; Costs; Enterprise resource planning; Job shop scheduling; Optimization methods; Pareto optimization; Petroleum industry; Production; Road vehicles; Routing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
  • Conference_Location
    Mumbai
  • Print_ISBN
    1-4244-0726-5
  • Electronic_ISBN
    1-4244-0726-5
  • Type

    conf

  • DOI
    10.1109/ICIT.2006.372715
  • Filename
    4238037