in this study, under the constraint of resource-saving and environment-friendliness objective, based on multi-agent genetic algorithm, multi-objective spatial optimization (moso) model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the competitive-cooperative relationship. the model was applied to solve the practical m...

in this paper, a new enhanced version of the particle swarm optimization (pso) is presented. an important modification is made by adding probabilistic functions into pso, and it is named probabilistic particle swarm optimization (ppso). since the variation of the velocity of particles in pso constitutes its search engine, it should provide two phases of optimization process which are: explorati...

introduction: variable resolution x-ray (vrx) ct is a new type of ct that can image objects at various spatial resolutions. in a vrx ct scanner, the spatial resolution increases at the cost of reduction in the field of view (fov). an important factor that limits the spatial resolution of the vrx ct is the effect of focal spot size. also, the optimum magnification is different at each incident a...

Introduction: Variable resolution x-ray (VRX) CT is a new type of CT that can image objects at various spatial resolutions. In a VRX CT scanner, the spatial resolution increases at the cost of reduction in the field of view (FOV). An important factor that limits the spatial resolution of the VRX CT is the effect of focal spot size. Also, the optimum magnification is different at each incident a...

beneficial management practices (bmps) are important measures for reducing agricultural non-point source (nps) pollution. however, selection of bmps for placement in a watershed requires optimizing available resources to maximize possible water quality benefits. due to its iterative nature, the optimization typically takes a long time to achieve the bmp trade-off results which is not desirable ...

Based on introducing two optimization algorithms, group search optimization (GSO) algorithm and particle swarm optimization (PSO) algorithm, a new hybrid optimization algorithm which named particle swarm-group search optimization (PS-GSO) algorithm is presented and its application to optimal structural design is analyzed. The PS-GSO is used to investigate the spatial truss structures with discr...

in recent years, due to absence of integrated watershed management in most regions, natural resources have witnessed numerous damages with severe floods as one of its consequences which further leads to economic, social and environmental damages. presently, there is no optimal utilization of land in most watersheds hence no optimal model matching with facilities and objectives is used in the wa...

land-use spatial allocation is a multi-objective collaborative spatial optimization methodfor rational use of the land use. based on global search capabilities and the information feedbackmechanism of ant colony optimization (aco), a land-use spatial allocation model (aco-la) isproposed. firstlyfirst, a construction graph is built for modeling the land-use spatial allocationproblem. secondlysec...

in this paper, the problem of simultaneous shape and size optimization of single-layer barrel vault frames which contains both of discrete and continuous variables is addressed. in this method, the improved magnetic charged system search (imcss) is utilized as the optimization algorithm and the open application programming interface (oapi) plays the role of interfacing analysis software with th...