in this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. scheduling algorithms play an important role in grid computing, parallel tasks scheduling and sending them to appr...

Many applications|from planning and scheduling to problems in molecular biology|rely heavily on a temporal reasoning component. In this paper, we discuss the design and an empirical analysis of algorithms for a temporal reasoning system based on Allen's innuential interval-based framework for representing temporal information. At the core of the system are algorithms for determining whether the...

Many applications from planning and scheduling to problems in molecular biology rely heavily on a temporal reasoning component In this paper we discuss the design and empirical analysis of algorithms for a temporal reasoning system based on Allen s in uential interval based framework for representing temporal information At the core of the system are algorithms for determining whether the tempo...

Response surface methodology is a common tool in optimizing processes. It mainly concerns situations when there is only one response of interest. However, many designed experiments often involve simultaneous optimization of several quality characteristics. This is called a Multiresponse Surface Optimization problem. A common approach in dealing with these problems is to apply desirability funct...

this paper describes a methodology in designing high-performance concrete for simply supported beams, using a hybrid optimization strategy based on a variable neighborhood search threshold acceptance algorithm. three strategies have been applied to discrete optimization of reinforced concrete beams: variable neighborhood descent (vnd), reduced neighborhood search (rns) and basic variable neighb...

Presently, the introduction of intelligent models to optimize structural problems has become an important issue in civil engineering and almost all other fields of engineering. Optimization models in artificial intelligence have enabled us to provide powerful and practical solutions to structural optimization problems. In this study, a novel method for optimizing structures as well as solving s...

In [1] (Hybrid Conjugate Gradient Algorithm for Unconstrained Optimization J. Optimization. Theory Appl. 141 (2009) 249 - 264), an efficient hybrid conjugate gradient algorithm, the CCOMB algorithm is proposed for solving unconstrained optimization problems. However, the proof of Theorem 2.1 in [1] is incorrect due to an erroneous inequality which used to indicate the descent property for the s...

In this paper, we study a combinatorial problem encountered in monetary systems. The problem concerned is to find an optimal solution R(k, n) of a combinatorial problem for some positive integers k and n. To the authors’ knowledge, there is no efficient solutions for this problem in the literatures so far. We first show how to find an efficient recursive construction algorithm based on the back...

this paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. first, the problem is formulated as a mixed integer linear programming model. then, to solve large problem sizes, an artificial immune algorithm hybridized with a simple local search in form of simulated annealing is proposed. two experiments are carried out to evaluate th...