Jian-Chao Zeng

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This paper presents an improved particle swarm optimization algorithm with feasibility- based rules (FRIPSO) to solve mixed-variable constrained optimization problems. Different kinds of variables are dealt in different ways in FRIPSO algorithm. Constraint handling is based on simple feasibility-based rules without the use of a penalty function which is(More)
Particle swarm optimization (PSO) is swarm-based stochastic optimization originating from artificial life and evolutionary computation. The algorithm completes the optimization through following the personal best solution of each particle and the global best value of the whole swarm. This paper improved the standard PSO's evolution equation on the(More)
Terrain coverage is one of basic problems in swarm robotics. Terrain coverage algorithm based on wasp swarm is a novel terrain coverage algorithm which is inspired of wasp division labor expressed by wasp response threshold. This paper introduces the terrain coverage algorithm based on wasp swarm and applies a model of discrete stochastic process to analyze(More)
Due to the design knowledge discrepancy during collaborative design, conflicts can be revealed from the process of collaborative design decision. A critical element of collaborative design would be conflict resolution. The conflict resolution is correlative with both of the knowledge granulation and specific method provided. In this paper, granularity is(More)