response surface methodology is a common tool in optimizing processes. it mainly concerns situations when there is only one response of interest. however, many designed experiments often involve simultaneous optimization of several quality characteristics. this is called a multiresponse surface optimization problem. a common approach in dealing with these problems is to apply desirability funct...

economic dispatch with valve point effect and prohibited operating zones (pozs) is a non-convex and discontinuous optimization problem. harmony search (hs) is one of the recently presented meta-heuristic algorithms for solving optimization problems, which has different variants. the performances of these variants are severely affected by selection of different parameters of the algorithm. intel...

Digital speckle correlation method has not only been widely used in a variety of photometric mechanical scenarios, but also integrated with multiple disciplines. In the future, it will even be inextricably linked to Internet Things, autonomous driving, deep learning and other fields. For given hardware condition, is great significance improve efficiency integer-pixel search increase accuracy su...

Optimal point-to-point trajectory planning for planar redundant manipulator is considered in this study. The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Se...

The N-tuple method [4] is a statistical pattern recognition method, which decomposes a given pattern into several sets of n points, termed “N tuples”. The input connection mapping of the N-tuple classifier determines the sampling and defines the locations of the pattern matrix. Realizing the fact that the classification performance of the N-tuple classifier is highly dependant on the actual sub...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

gravitational search algorithm (gsa) is one of the newest swarm based optimization algorithms, which has been inspired by the newtonian laws of gravity and motion. gsa has empirically shown to be an efficient and robust stochastic search algorithm. since introducing gsa a convergence analysis of this algorithm has not yet been developed. this paper introduces the first attempt to a formal conve...