An optimal design of a linear antenna array is presented. The antenna array is optimized using a particle swarm optimization based method in order to produce a radiation pattern that has the minimum possible side lobe level and the maximum possible gain at the desired direction. The method has been applied to collinear wire-dipole arrays and seems to be suitable for improving the radiation patt...

AbsfracfThis paper introduces a particle swarm optimization-based method for solving a multi-objective generator maintenance scheduling problem with many constraints. It is shown that particle swarm optimizationbased approach is effective in obtaining feasible schedules in a reasonable time. Actual data from a practical power system was used in this study and results were compared against those...

The schema produces derogatory implications in its practical domain in that working with the elderly is considered as something inferior as “Working with older people is seen as focusing on custodial activities that lack the “excitement” and status of other fields of social work practice” [3]. The schema and its associative labels have also given rise to a loss of voice for the elderly in that ...

An algorithm is presented for the fast and accurate definition of protein structural domains from coordinate data without prior knowledge of the number or type of domains. The algorithm explicitly locates domains that comprise one or two continuous segments of protein chain. Domains that include more than two segments are also located. The algorithm was applied to a nonredundant database of 230...

I argue that taking the Practical Conditionals Thesis (PCT) seriously demands a new understanding of the semantics of such conditionals. Practical Conditionals Thesis: A practical conditional [if A][ought(B)] expresses B’s conditional preferability given A Paul Weirich has argued that the conditional utility of a state of affairs B on A is to be identified as the degree to which it is desired u...

Particle swarm optimization is a popular method for solving difficult optimization problems. There have been attempts to formulate the method in formal probabilistic or stochastic terms (e.g. bare bones particle swarm) with the aim to achieve more generality and explain the practical behavior of the method. Here we present a Bayesian interpretation of the particle swarm optimization. This inter...

Multi-objective open-shop scheduling is definitely significant in practical. However, the research focused on multi-objective open-shop scheduling was relatively scarce. This article proposed a particle swarm optimization to address open-shop scheduling problems with multiple objectives. Originally, particle swarm optimization was invented to treat continuous optimization problems. In this pape...

The present paper extends the idea of job shop scheduling problem with resting constraints to the train scheduling problem with the Muslim praying considerations. For this purpose, after proposing the new mathematical model, a heuristic algorithm based on the Electromagnetism-Like algorithm (EM) which is well adjusted to scheduling problems is employed to solve the large-size practical cases. T...

The traditional methods such as critical path method (CPM) and linear programming (LP) have difficulty solving more general scheduling problems such as resource constrained scheduling problems. Emerging techniques such as particle swarm optimisation (PSO) have shown advantages in addressing this problem. However, the performance of simple PSO is greatly dependent on its parameters, and bad sele...

In this work the swarm behavior principles of Craig W. Reynolds are combined with deterministic traits. This is done by using leaders with motions based on space filling curves like Peano and Hilbert. Our goal is to evaluate how the swarm of agents works with this approach, supposing the entire swarm will better explore the entire space. Therefore, we examine di↵erent combinations of Peano and ...