A.J. Quist

TL;DR: The primal-dual affine scaling directions are used to escape from local maxima encountered during the evolutionary dynamics phase, and are combined with an evolutionary dynamics algorithm which generates primal-feasible paths along which the objective is monotonically improved until a local solution is reached.

TL;DR: This paper considers general, typically nonconvex, Quadratic programming Problem, and the Semidefinite relaxation proposed by Shor provides bounds on the optimal solution, but it does not always provide sufficiently strong bounds if linear constraint are also involved.

TL;DR: In this paper, mixed-integer nonlinear programming (MINLP) is used as the optimization method for determining optimal loading schemes in nuclear reactor fuel management, and it is shown that MINLP combined with local search heuristics is a promising approach to fuel management optimization.

TL;DR: Several adaptations and model adjustments are described that make the model tractable for a general nonlinear mixed-integer solver to search for optimal fuel loading schemes to solve the nuclear reactor fuel management problem.

TL;DR: Fuel shuffling optimization procedures are proposed for the Hoger Onderwijs Reactor in Delft, The Netherlands, a 2MWth swimming-pool type research reactor based on the multiple cyclic interchange approach, according to which the search for the reload pattern associated with the highest objective function value can be thought of as divided in multiple stages.