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Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF). Every agent in SKF is regarded as a Kalman filter. Based on the mechanism of Kalman filtering and measurement process, every agent estimates the global minimum/maximum. Measurement, which is required in Kalman filtering, is mathematically...
Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. Later, binary gravitational search algorithm (BGSA) is designed to solve discrete optimization problems. In this study, rule-based multi-state gravitational...
The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. Many improvements of the binary-based algorithms have been reported. In this paper, a variant of GSA called multi-state gravitational search algorithm (MSGSA) for discrete optimization problems is proposed. The MSGSA concept is based on a simplified mechanism...
Particle swarm optimization (PSO) has been successfully applied to solve various optimization problems. Recently, a state-based algorithm called multi-state particle swarm optimization (MSPSO) has been proposed to solve discrete combinatorial optimization problems. The algorithm operates based on a simplified mechanism of transition between two states. However, the MSPSO algorithm has to deal with...
Assembly sequence planning (ASP) becomes one of the major challenges in product design and manufacturing. A good assembly sequence leads to reduced costs and duration in the manufacturing process. However, assembly sequence planning is known to be a classical NP-hard combinatorial optimization problem; ASP with many product components becomes more difficult to solve. In this paper, an approach based...
The process of designing a set of good DNA sequences is an essential problem and one of the most practical and important research topics in DNA-based computing and the DNA nanotechnology area. In this field of research, a DNA sequence design problem is defined as a multi-objective problem, and it is evaluated using four objective functions, h-measure, similarity, continuity and hairpin. In addition,...
Particle swarm optimization (PSO) has been widely used to solve real-valued optimization problems. A variant of PSO, namely, binary particle swarm optimization (BinPSO) has been previously developed to solve discrete optimization problems. Later, many studies have been done to improve BinPSO in term of convergence speed, stagnation in local optimum, and complexity. In this paper, a novel multi-state...
This paper presents a novel algorithm, which is based on Gravitational Search Algorithm (GSA), for multiobjective optimization problems. The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. In particular, a population of particles corresponds to one objective function to be minimized or maximized. Simultaneous minimization...
Generally, in DNA computing, the DNA sequences used for the computation should be critically designed in order to reduce error that could occur during computation. Previously, direct-proportional length-based DNA computing which involved DNA sequences with different lengths has been implemented to solve the shortest path problem. In this study, particle swarm optimization (PSO) and population-based...
It is well-known that thresholding algorithm is needed by gray-scale images in segmentation operation. In this paper, real printed circuit boards used are captured using a monochrome charged coupled device camera and produced images consisting of foreground and background objects in gray-scale format. In order to correctly differentiate these two kinds of attributes, several of thresholding algorithms...
Manipulation of wire sizing, buffer sizing, and buffer insertion are a few techniques that can be used to improve time delay in very large scale integration (VLSI) circuit routing. This paper enhances an existing approach, which is based on Particle Swarm Optimization (PSO) for solving routing problem in VLSI circuits. A two-step Binary Particle Swarm Optimization (BPSO) approach, which is based on...
The performance of very large scale integration (VLSI) circuits is depends on the interconnected routing in the circuits. In VLSI routing, wire sizing, buffer sizing, and buffer insertion are techniques to improve power dissipation, area usage, noise, crosstalk, and time delay. Without considering buffer insertion, the shortest path in routing is assumed having the minimum delay and better performance...
Most of the operational time of a PCB Robotic Drill is spent on moving the drill bit between the holes. This operational time can be kept at a minimal level by optimizing the route taken by the robot. An optimized route translates to a minimal cost of operating the robot. This paper proposes a new model that implements Particle Swarm Optimization (PSO) in order to find optimized routing path when...
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