This paper deals with the flow shop scheduling problem. To find optimal solution is an NP-hard The reviews some algorithms from literature and applies a benchmark dataset to evaluate their efficiency. In this research work, discrete bacterial memetic evolutionary algorithm (DBMEA) as global searcher was investigated. proposed improves local search by applying simulated annealing (SA). presents ...

in regions with deficient or no data, it is necessary to apply indirect methods to estimate the peak flow. regional flood analysis is the most accurate and reliable technique in such cases. one of the regional flood methods for flood analysis in arid and semi arid regions is hybrid technique, which was applied on data of khorasan razavi province watersheds to estimate the peak flow. hybrid meth...

We resolve an open question raised by Feige & Scheideler by showing that the best known approximation algorithm for flow shops is essentially tight with respect to the used lower bound on the optimal makespan. We also obtain a nearly tight hardness result for the general version of flow shops, where jobs are not required to be processed on each machine. Similar results hold true when the object...

Web based systems have been shown to be useful tools for supporting educational communication for teachers and students. In this paper we present such a system, which is an Integrated Distributed Learning Environment (IDLE). We present the technical description of this IDLE and we discuss its main characteristics like the transmission of multimedia data over the network, the manipulation of the...

The Mixed No-Idle Flow-shop Scheduling Problem (MNIFSP) is an extension of flow-shop scheduling, which has practical significance and application prospects in production scheduling. To improve the efficacy solving complicated multiobjective MNIFSP, a MultiDirection Update (MDU) based Multiobjective Particle Swarm Optimization (MDU-MoPSO) proposed this study. For biobjective optimization problem...

We consider the NP-hard problem of scheduling n jobs in m two-stage parallel flow shops so as to minimize the makespan. This problem decomposes into two subproblems: assigning the jobs to parallel flow shops; and scheduling the jobs assigned to the same flow shop by use of Johnson’s rule. For m = 2, we present a 32 -approximation algorithm, and for m = 3, we present a 12 7 -approximation algori...