Simulated annealing’s high computational intensity has stimulated researchers to experiment with various parallel and distributed simulated annealing algorithms for shared memory, message-passing, and hybrid-parallel platforms. MapReduce is an emerging distributed computing framework for large-scale data processing on clusters of commodity servers; to our knowledge, MapReduce has not been used ...

abstract: in this paper, an exergy analysis approach is proposed for optimal design of distillation column by using simulated annealing algorithm. first, the simulation of a distillation column was performed by using the shortcut results and irreversibility in each tray was obtained. the area beneath the exergy loss profile was used as irreversibility index in the whole column. then, first opti...

this paper deals with the problem of user-server assignment in online social network systems. online social network applications such as facebook, twitter, or instagram are built on an infrastructure of servers that enables them to communicate with each other. a key factor that determines the facility of communication between the users and the servers is the expected transmission time (ett). a ...

modeling of fermentation processes is so complicated and uncertain; therefore it is necessary to provide a robust and appropriate dynamic optimization method. in order to obtain the maximum amount of yeast (saccharomyces cerevisiae), the bioreactor must be operated under optimal conditions. to determine substrate feeding in a fed-batch bioreactor, a simulated annealing (sa) approach was examine...

Reliable safety critical systems are designed for fault tolerance and impose high dependability with reliability requirements. Scheduling such systems is hard in traditional event triggered systems and becomes difficult as complexity increases. Time triggered systems with timing guaranteed in task activation, avoiding the risk of missing a hard-critical deadline, overcoming the problem of time ...

Traditionally the machine-learning community has viewed the No Free Lunch (NFL) theorems for search and optimization as a limitation. We review, analyze, and unify the NFL theorem with the perspectives of ``blind"" search and meta-learning to arrive at necessary conditions for improving black-box optimization. We survey meta-learning literature to determine when and how meta-learning can benefi...

In this work, we propose a Hybrid particle swarm optimization-Simulated annealing algorithm and present a comparison with i) Simulated annealing algorithm and ii) Back propagation algorithm for training neural networks. These neural networks were then tested on a classification task. In particle swarm optimization behaviour of a particle is influenced by the experiential knowledge of the partic...