in some industries as foundries, it is not technically feasible to interrupt a processor between jobs. this restriction gives rise to a scheduling problem called no-idle scheduling. this paper deals with scheduling of no-idle open shops to minimize maximum completion time of jobs, called makespan. the problem is first mathematically formulated by three different mixed integer linear programming...

A Monte Carlo simulated annealing algorithm based on the generalized entropy of Tsallis is presented. The algorithm obeys detailed balance and reduces to a steepest descent algorithm at low temperatures. Application to the conformational optimization of a tetrapeptide demonstrates that the algorithm is more effective in locating low energy minima than standard simulated annealing based on molec...

Multiobjective optimization is a common problem in the field of industrial cutting. In actual production settings, it necessary to rely on experience skilled workers achieve multiobjective collaborative optimization. The process intelligence perceive parameters cut object through sensors and use machines instead manual decision making. However, traditional sequential algorithm cannot satisfy pr...

in this paper an application of cellular learning automata (cla) to vlsi placement is presented. the cla, which is introduced for the first time in this paper, is different from standard cellular learning automata in two respects. it has input and the cell neighborhood varies during the operation of cla. the proposed cla based algorithm for vlsi placement is tested on number of placement proble...

Since there is a longitudinal and horizontal penetration problem between multi-level data centers in the smart grid information transmission network. Based on improved Simulated Annealing algorithm, this paper proposes storage optimization model for grids based Hadoop architecture. Combining characteristics of distributed cloud computing, are equivalent to task-oriented set. The platform flatte...

Task scheduling in an important element a distributed system. It is vital how the jobs are correctly assigned for each computer’s processor to improve performance. The presented approaches attempt reduce expense of optimizing use CPU. These techniques mostly lack planning and need be comprehensive. To address this fault, hybrid optimization technique proposed hybridization both First-Come First...

Job scheduling system problem is a core and challenging issue in cloud computing. How to use cloud computing resources efficiently and gain the maximum profits with job scheduling system is one of the cloud computing service providers’ ultimate goals. For characteristics of particle swarm optimization algorithm in solving the large-scale combination optimization problem easy to fall into the se...