Global solution of multi-objective optimal control problems with multi agent collaborative search and direct finite elements transcription

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This paper addresses the solution of optimal control problems with multiple and possibly conflicting objective functions. The solution strategy is based on the integration of Direct Finite Elements in Time (DFET) transcription into the Multi Agent Collaborative Search (MACS) framework. Multi Agent Collaborative Search is a memetic algorithm in which a population of agents performs a set of individual and social actions looking for the Pareto front. Direct Finite Elements in Time transcribe an optimal control problem into a constrained Non-linear Programming Problem (NLP) by collocating states and controls on spectral bases. MACS operates directly on the NLP problem and generates nearly-feasible trial solutions which are then submitted to a NLP solver. If the NLP solver converges to a feasible solution, an updated solution for the control parameters is returned to MACS, along with the corresponding value of the objective functions. Both the updated guess and the objective function values will be used by MACS to generate new trial solutions and converge, as uniformly as possible, to the Pareto front. To demonstrate the applicability of this strategy, the paper presents the solution of the multi-objective extensions of two well-known space related optimal control problems: the Goddard Rocket problem, and the maximum energy orbit rise problem.
Original languageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation, (CEC)
Place of PublicationPiscataway
Number of pages8
ISBN (Print)9781509006236
Publication statusPublished - 21 Nov 2016
Event2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016


Conference2016 IEEE Congress on Evolutionary Computation, CEC 2016
Abbreviated titleIEEE CEC 2016
Internet address



  • optimal control
  • optimisation
  • aerospace engineering
  • space access
  • launch vehicle
  • finite elements in time (FET)
  • collaboration
  • programming

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