2013
DOI: 10.1016/j.ast.2012.02.021
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A particle swarm approach for flight path optimization in a constrained environment

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Cited by 29 publications
(12 citation statements)
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“…Changing the position and velocity of each particle at each iteration works as follows. Assume that the l-th particle has position vector x l (t) and velocity vector v l (t) [5]. Then, the updated velocity v l (t + 1) will be:…”
Section: Search Algorithmsmentioning
confidence: 99%
“…Changing the position and velocity of each particle at each iteration works as follows. Assume that the l-th particle has position vector x l (t) and velocity vector v l (t) [5]. Then, the updated velocity v l (t + 1) will be:…”
Section: Search Algorithmsmentioning
confidence: 99%
“…In their experiment, the first-phase heuristic is able to screen out infeasible solutions, and pass the feasible intermediated solution to further optimise with less computational effort. Blasi et al [64] presented a sampling density threshold PSO to avoid the particles crowding problem for a 2-dimensional flight trajectory optimisation which can denote non-circular and concave obstacles taking into account the flight dynamic. The objective of Traffic Management in a Terminal Manoeuvring Area / Terminal Manoeuvring Centre (TMA/TMC) is to maintain a vital balance between smooth air traffic flow and the capacity of surface traffic operation in an airport.…”
Section: Flight Path Optimisationmentioning
confidence: 99%
“…Calculus of variation is a technique used to solve the problems appearing in diverse fields, eg., dynamics of rigid body, optimization of orbit [10], flight design [9,13], etc. Optimality conditions and duality results for various classes of nonconvex variational problems have been of much interest in recent years, and several contributions have been made to its development (see, for example, [1,6,12,14,15,20]).…”
Section: Introductionmentioning
confidence: 99%