this paper considers the problem of scheduling hybrid flowshops with machine availability constraints (mac) to minimize makespan. the paper deals with a specific case of mac caused by preventive maintenance (pm) operations. contrary to previous papers considering fixed or/and conservative policies, we explore a case in which pm activities might be postponed or expedited while necessary. regardi...

nowadays, economic load dispatch between generation units with least cost involved is one of the most important issues in utilizing power systems. in this paper, a new method i.e. water cycle algorithm (wca) which is similar to other intelligent algorithm and is based on swarm, is employed in order to solve the economic load dispatch problem between power plants. wca is used to solve complicate...

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...

for a uniform distribution of water, decrease in water waste and decrease in erosion of soil, it is important that a land be prepared with proper slopes along its length as well as width. the aim of leveling is to create appropriate slopes for irrigation and drainage on the lands that were not already properly levelled and of the same time creating the level surface with a minimum transport of ...

background: dose calculation algorithms play a very important role in predicting the explicit dose distribution. we evaluated the percent depth dose (pdd), lateral depth dose profile, and surface dose volume histogram in inhomogeneous media using calculation algorithms and inhomogeneity correction methods. materials and methods: the homogeneous and inhomogeneous virtual slab phantoms used in th...

it is well known that if the coefficient matrix in a linear system is large and sparse or sometimes not readily available, then iterative solvers may become the only choice. the block solvers are an attractive class of iterative solvers for solving linear systems with multiple right-hand sides. in general, the block solvers are more suitable for dense systems with preconditioner. in this paper,...

recently, data collection from seabed by means of underwater wireless sensor networks (uwsn) has attracted considerable attention. autonomous underwater vehicles (auvs) are increasingly used as uwsns in underwater missions. events and environmental parameters in underwater regions have a stochastic nature. the target area must be covered by sensors to observe and report events. a ‘topology cont...

Global optimization methods play an important role to solve many real-world problems. Flower pollination algorithm (FP) is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new hybrid optimization method called hybrid flower pollination algorithm (FPPSO) is proposed. The method combines the standard flower pollination algorithm (FP) with the par...

The cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. To enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. Normally, the parametersof the cuckoo search are kept constant. This may lead todecreasing the efficiency of the algorithm. To cop...

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...