This paper considers the problem of tracking a mobile target in an obstructive environment using a swarm of simple robots with limited sensing and communicating abilities. The target-tracking procedure, which has not been paid attention in previous swarm robotic researches, is specially focused. In tracking phase of problem, the swarm should move with low energy cost while keeping the target in...

Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search techniqu...

In view of shortcomings of the particle swarm optimization algorithm such as poor late optimization ability and proneness to local optimization etc, this paper proposes an opposition-based learning particle swarm optimization (OBLPSO) algorithm for the optimization of logistics distribution routes, firstly, establishes a logistics distribution route optimization mathematical model, and then sol...

In this paper an extensive theoretical and empirical analysis of recently introduced Particle Swarm Optimization algorithm with Convergence Related parameters (CR-PSO) is presented. The convergence of the classical PSO algorithm is addressed in detail. The conditions that should be imposed on parameters of the algorithm in order for it to converge in mean-square have been derived. The practical...

In this paper, we present a Binary cat swarm optimization for solving the Set covering problem. The Set covering problem is a well-known NP-hard problem with many practical applications, including those involving scheduling, production planning and location problems. Binary cat swarm optimization is a recent swarm metaheuristic technique based on the behaviour of discrete cats. Domestic cats sh...

The optimization of job-shop scheduling is very important because of its theoretical and practical significance. In this paper, a computationally effective approach of combining bacterial foraging strategy with particle swarm optimization for solving the minimum makespan problem of job shop scheduling is proposed. In the artificial bacterial foraging system, a novel chemotactic model is designe...

This paper presents new solution methods and results based on a refined binary particle swarm optimization (RBPSO) for solving the generation/pumping scheduling problem within the power system operation with pumped-storage units. The proposed RBPSO approach combines a basic particle swarm optimization (PSO) with binary encoding/decoding techniques. Complete solution algorithms and encoding/deco...

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a...

An attempt has been made by incorporating some special features in the conventional particle swarm optimization (PSO) technique and its usefulness was tested in a common control application involving PID controller tuning. This algorithm differs from the existing PSO methods in the inclusion of unbiased search approach of the swarm particles without establishing inter-particle communication in ...

We present a novel hybrid method, swarm intelligence based sample average approximation (SIBSAA), for solving the capacitated reliable facility location problem (CRFLP). The CRFLP extends the wellknown capacitated fixed-cost facility problem by accounting for the unreliability of facilities. The standard SAA procedure, while effectively used in many applications, can lead to poor solution quali...