Locating a bioenergy facility using a hybrid optimization method

Athanasios A. Rentizelas, Ilias P. Tatsiopoulos

Research output: Contribution to journalArticle

54 Citations (Scopus)

Abstract

In this paper, the optimum location of a bioenergy generation facility for district energy applications is sought. A bioenergy facility usually belongs to a wider system, therefore a holistic approach is adopted to define the location that optimizes the system-wide operational and investment costs. A hybrid optimization method is employed to overcome the limitations posed by the complexity of the optimization problem. The efficiency of the hybrid method is compared to a stochastic (genetic algorithms) and an exact optimization method (Sequential Quadratic Programming). The results confirm that the hybrid optimization method proposed is the most efficient for the specific problem. (C) 2009 Elsevier B.V. All rights reserved.

LanguageEnglish
Pages196-209
Number of pages14
JournalInternational Journal of Production Economics
Volume123
Issue number1
DOIs
Publication statusPublished - Jan 2010

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Quadratic programming
Genetic algorithms
Bioenergy
Costs
Genetic algorithm
Optimization problem
Hybrid method
Holistic approach
Energy

Keywords

  • hybrid optimization
  • genetic algorithms
  • bioenergy facility
  • supply chain
  • optimization methods
  • facility location
  • biomass logistics
  • heuristic methods

Cite this

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title = "Locating a bioenergy facility using a hybrid optimization method",
abstract = "In this paper, the optimum location of a bioenergy generation facility for district energy applications is sought. A bioenergy facility usually belongs to a wider system, therefore a holistic approach is adopted to define the location that optimizes the system-wide operational and investment costs. A hybrid optimization method is employed to overcome the limitations posed by the complexity of the optimization problem. The efficiency of the hybrid method is compared to a stochastic (genetic algorithms) and an exact optimization method (Sequential Quadratic Programming). The results confirm that the hybrid optimization method proposed is the most efficient for the specific problem. (C) 2009 Elsevier B.V. All rights reserved.",
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Locating a bioenergy facility using a hybrid optimization method. / Rentizelas, Athanasios A.; Tatsiopoulos, Ilias P.

In: International Journal of Production Economics, Vol. 123, No. 1, 01.2010, p. 196-209.

Research output: Contribution to journalArticle

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AU - Rentizelas, Athanasios A.

AU - Tatsiopoulos, Ilias P.

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AB - In this paper, the optimum location of a bioenergy generation facility for district energy applications is sought. A bioenergy facility usually belongs to a wider system, therefore a holistic approach is adopted to define the location that optimizes the system-wide operational and investment costs. A hybrid optimization method is employed to overcome the limitations posed by the complexity of the optimization problem. The efficiency of the hybrid method is compared to a stochastic (genetic algorithms) and an exact optimization method (Sequential Quadratic Programming). The results confirm that the hybrid optimization method proposed is the most efficient for the specific problem. (C) 2009 Elsevier B.V. All rights reserved.

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KW - optimization methods

KW - facility location

KW - biomass logistics

KW - heuristic methods

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