Cooling schedules for optimal annealing
Mathematics of Operations Research
Local Search in Combinatorial Optimization
Local Search in Combinatorial Optimization
Fitness Landscapes, Memetic Algorithms, and Greedy Operators for Graph Bipartitioning
Evolutionary Computation
Multipoint communication: a survey of protocols, functions, and mechanisms
IEEE Journal on Selected Areas in Communications
Landscape analysis for multicast routing
Computer Communications
Genetic local search for multicast routing with pre-processing by logarithmic simulated annealing
Computers and Operations Research
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We describe a population-based search algorithm for cost minimization of multicast routing. The algorithm utilizes the partially mixed crossover operation (PMX) and a landscape analysis in a pre-processing step. The aim of the landscape analysis is to estimate the depth Γ of the deepest local minima in the landscape generated by the routing tasks and the objective function. The analysis employs simulated annealing with a logarithmic cooling schedule (LSA). The local search performs alternating sequences of descending and ascending steps for each individual of the population, where the length of a sequence with uniform direction is controlled by the estimated value of Γ. We present results from computational experiments on a synthetic routing tasks, and we provide experimental evidence that our genetic local search procedure, that combines LSA and PMX, performs better than algorithms using either LSA or PMX only.