this paper investigates the problem of just-in-time permutation flow shop scheduling with limited buffers and linear job deterioration in an uncertain environment. the fuzzy set theory is applied to describe this situation. a novel mixed-integer nonlinear program is presented to minimize the weighted sum of fuzzy earliness and tardiness penalties. due to the computational complexities, the prop...

The results of a study on incorporating solar-thermal collectors into a hybrid renewable energy system are reported. A photovoltaic–wind turbine–fuel cell–solar-thermal collector system is designed and an economic model is introduced for supplying the residential thermal and electrical loads via the grid-connected hybrid system. Since determining the optimal operation of a hybrid system such as...

This paper presents a genetic algorithm for an important computational biology problem. The problem appears in the computational part of a new proposal for DNA sequencing denominated sequencing by hybridization. The general usage of this method for real sequencing purposes depends mainly on the development of good algorithmic procedures for solving its computational phase. The proposed genetic ...

this paper uses integrated data envelopment analysis (dea) models to rank all extreme and non-extreme efficient decision making units (dmus) and then applies integrated dea ranking method as a criterion to modify genetic algorithm (ga) for finding pareto optimal solutions of a multi objective programming (mop) problem. the researchers have used ranking method as a shortcut way to modify ga to d...

  In this paper flexible job-shop scheduling problem (FJSP) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. As the problem belongs to the class of NP-Hard problems, a new hybrid genetic algorithm is proposed to obtain a large set of Pareto-optima...

This paper presents a genetic algorithm for a scheduling problem frequent in printed circuit board manufacturing: a hybrid flowshop with unrelated machines, sequence dependent setup time and machine availability constraints. The proposed genetic algorithm is a modified version of previously proposed genetic algorithms for the same problem. Experimental results show the advantages of using new c...

Hybrid flow-shop or flexible flow shop problems have remained subject of intensive research over several years. Hybrid flow-shop problems overcome one of the limitations of the classical flow-shop model by allowing parallel processors at each stage of task processing. In many papers the assumptions are generally made that there is unlimited storage available between stages and the setup times a...

Wireless Sensor Network WSN deployment is an active research area. Its goal to deploy sensors in certain environment efficiently optimize some evaluation measures. Meta heuristic searching optimization approaches have been proven be effective solving problem. They strong power exploring the solution space and converging toward theoptimal region. One key factor achieving more meta-heuristic sele...

Let a graph G = (V;E) be given. In the path center problem we want to find a path P in G such that the maximum weighted distance of P to every vertex in V is minimized. In this paper a genetic algorithm and ahybrid of genetic and ant colony algorithms are presented for the path center problem. Some test problems are examined to compare the algorithms. The results show that for almost all exampl...