Flexible job-shop scheduling problem (FJSP) is very important in many research fields such
as production management and combinatorial optimization. The FJSP problems cover two …

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This study presents an adaptive two-layer particle swarm optimization algorithm with elitist
learning strategy (ATLPSO-ELS), which has better search capability than classical particle …

In this paper, we propose a new variant of particle swarm optimization (PSO), namely PSO
with increasing topology connectivity (PSO-ITC), to solve unconstrained single-objective …

Scheduling can be defined as the allocation of available resources over time while
optimising a set of criteria like early completion time of task, holding inventory, etc. The …

Most of the recent proposed particle swarm optimization (PSO) algorithms do not offer the
alternative learning strategies when the particles fail to improve their fitness during the …

Particle swarm optimization (PSO) has shown its competitive performance for solving
benchmark and real-world optimization problems. Nevertheless, it requires better control of …

Large-scale global optimization (LSGO) is a very important but thorny task in optimization
domain, which widely exists in management and engineering problems. In order to …

Particle swarm optimization (PSO) is a popular method widely used in solving different
optimization problems. Unfortunately, in the case of complex multidimensional problems …

Particle swarm optimization (PSO) is a well-known algorithm for global optimization over
continuous search spaces. However, this algorithm is limited by the intense conflict between …