this study focuses on the forecasting of energy demands of residential and commercial sectors using linear and exponential functions. the coefficients were obtained from genetic and particle swarm optimization (pso) algorithms. totally, 72 different scenarios with various inputs were investigated. consumption data in respect of residential and commercial sectors in iran were collected from the ...

Evrimsel Algoritmalar (EA’lar), ağ tasarımı problemleri, yol bulma sosyal ve ekonomik planlama gibi karmaşık optimizasyon problemlerini çözmek için yaygın olarak kullanılan algoritmalardır. Kullandıkları akıllı yöntemler sayesinde EA’lar, yeni çözümler üretmek ilk çözümü, yinelemeli olarak, iyileştirirler. Sıklıkla EA'lardan biri Parçacık Sürü Optimizasyonu (PSO) algoritmasıdır. PSO algoritması...

Quantum-behaved particle swarm optimization (QPSO) algorithm is a global convergence guaranteed algorithms, which has been applied widely for continuous optimization problems. In this paper, we propose an improved quantum-behaved particle swarm optimization with memory according to the means of best position of particles and using sigal step seaching strategy for sovle the multidimentional prob...

In light of the accuracy of particle swarm optimization-particle filter (PSO-PF) inadequate for multi-robot cooperative positioning, the paper presents population density particle swarm optimization-particle filter (PDPSO-PF), which draws cooperative coevolutionary algorithm in ecology into particle swarm optimization. By taking full account of the competitive relationship between the environme...

In this paper, a particle swarm optimization algorithm (PSO) is presented to solve the permutaion flowshop sequencing problem (PFSP) with the objectives of minimizing makespan and maximum lateness of jobs, respectively. Simple but very efficient local search based on variable neighborhood search (VNS) is embedded in the particle swarm optimization algorithm to solve the well known benchmark sui...

Bilinear models can approximate a large class of nonlinear systems adequately and usually with considerable parsimony in the number of coefficients required. This paper presents the application of Particle Swarm Optimization (PSO) algorithm to solve both offline and online parameter estimation problem for bilinear systems. First, an Adaptive Particle Swarm Optimization (APSO) is proposed to inc...

This paper presents a Particle Swarm Optimization with Improved Inertia Wight (PSO-IIW) for Combined Heat and Power Economic Dispatch (CHPED) problem. The proposed PSO-IIW technique, which is a population based global search and optimization technique, has been developed to solve the CHPED problem. The CHPED problem is formulated as an optimization problem which is solved by the PSO-IIW techniq...

Vehicle Routing Problem (VRP) is addressed to a class of problems for determining a set of vehicle routes, in which each vehicle departs from a given depot, serves a given set of customers, and returns back to the same depot. On the other hand, simultaneous delivery and pickup problems have drawn much attention in the past few years due to its high usage in real world cases. This study, therefo...