Evolutionary membrane computing: A comprehensive survey and new results
; Evolutionary computation
; Evolutionary membrane computing
; Membrane-inspired evolutionary algorithm
; Automated design of membrane computing model
; Optimisation problems
; Multiobjective optimisation
; Differential evolution
; Automatic design
MetadataShow full item record
AbstractEvolutionary membrane computing is an important research direction of membrane computing that aims to explore the complex interactions between membrane computing and evolutionary computation. These disciplines are receiving increasing attention. In this paper, an overview of the evolutionary membrane computing state-of-the-art and new results on two established topics in well defined scopes (membrane-inspired evolutionary algorithms and automated design of membrane computing models) are presented. We survey their theoretical developments and applications, sketch the differences between them, and compare the advantages and limitations. (C) 2014 Elsevier Inc. All rights reserved.
VersionNo full-text in the repository
CitationZhang GX, Gheorghe M, Pan LQ et al (2014) Evolutionary membrane computing: A comprehensive survey and new results. Information Sciences. 279: 528-551.
Link to publisher’s versionhttps://doi.org/10.1016/j.ins.2014.04.007
Showing items related by title, author, creator and subject.
A modified membrane-inspired algorithm based on particle swarm optimization for mobile robot path planningWang, X.; Zhang, G.; Zhao, J.; Rong, H.; Ipate, F.; Lefticaru, Raluca (2015-10)To solve the multi-objective mobile robot path planning in a dangerous environment with dynamic obstacles, this paper proposes a modified membraneinspired algorithm based on particle swarm optimization (mMPSO), which combines membrane systems with particle swarm optimization. In mMPSO, a dynamic double one-level membrane structure is introduced to arrange the particles with various dimensions and perform the communications between particles in different membranes; a point repair algorithm is presented to change an infeasible path into a feasible path; a smoothness algorithm is proposed to remove the redundant information of a feasible path; inspired by the idea of tightening the fishing line, a moving direction adjustment for each node of a path is introduced to enhance the algorithm performance. Extensive experiments conducted in different environments with three kinds of grid models and five kinds of obstacles show the effectiveness and practicality of mMPSO.
Membrane Computing Models: ImplementationsZhang, G.; Pérez-Jiménez, M.J.; Riscos-Núñez, A.; Verlan, S.; Konur, Savas; Hinze, T.; Gheorghe, Marian (Springer, 2021)Presents comprehensive descriptions of the most significant membrane computing tools developed for various models Describes the most relevant applications, facilitating a better understanding of how the tools are used in building, experimenting with and analysing membrane computing models of complex problems arising in robotics, automatic design of P systems, image processing, ecosystem modelling, systems and synthetic biology, and bioinformatics Discusses efficient software and hardware solutions, together with the algorithms and platforms used