Abstract
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 Nonlinear Programming Problem (NLP) by collocating states and controls on spectral bases. MACS operates directly on the NLP problem and generates nearlyfeasible 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 multiobjective extensions of two wellknown space related optimal control problems: the Goddard Rocket problem, and the maximum energy orbit rise problem.
Original language  English 

Title of host publication  2016 IEEE Congress on Evolutionary Computation, (CEC) 
Place of Publication  Piscataway 
Publisher  IEEE 
Pages  869876 
Number of pages  8 
ISBN (Print)  9781509006236 
DOIs  
Publication status  Published  21 Nov 2016 
Event  2016 IEEE Congress on Evolutionary Computation, CEC 2016  Vancouver, Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016 http://www.wcci2016.org/ 
Conference
Conference  2016 IEEE Congress on Evolutionary Computation, CEC 2016 

Abbreviated title  IEEE CEC 2016 
Country/Territory  Canada 
City  Vancouver 
Period  24/07/16 → 29/07/16 
Internet address 
Keywords
 optimal control
 optimisation
 aerospace engineering
 space access
 launch vehicle
 finite elements in time (FET)
 collaboration
 programming
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Christie Maddock, PhD, FHEA, MRAeS
 Mechanical And Aerospace Engineering  Senior Lecturer
 Ocean, Air and Space
Person: Academic