The nonLinear conjugate gradient method solves issues of the frame: minimizef(x), x ∈,ℜ,employing an iterative plot, x(k+1) = x(k) + α, kd(k), where f is a non-polynomial function. We utilized two variants of the optimum Line search namely, direct and indirect methods, to compute the step-length in this paper. Both Line searches yielded great outcome when employed to a few unconstrained non-polynomial test functions.

Discrete-event simulation based optimization is the process of finding the optimum design of a stochastic system when the performance measure(s) could only be estimated via simulation. Randomness in simulation outputs often challenges the correct selection of the optimum. We propose an algorithm that merges Ranking and Selection procedures with a large class of random search methods for continuous simulation optimization problems. Under a mild assumption, we prove the convergence of the algorithm in probability to a global optimum. The new algorithm addresses the noise in simulation outputs while benefits the proven efficiency of random search methods.

In this paper the problem of optimal buffer size in a production Line is considered. A simulation-optimization model based on Tabu search algorithm is developed and implemented in one of the production Lines of Mashhad Wheel Manufacturing Company. In the model, tabu search is used to approach the global optima, avoiding the local optimum points. Using the model, it is shown that the overall buffer stock can be reduced by at least 10 percent. Considering the days prices, this amounts to nearly 31000000 Rials in savings.

In this paper, we solve unconstrained optimization problem using a free Line search steepest descent method. First, we propose a double parameter scaled quasi Newton formula for calculating an approximation of the Hessian matrix. The approximation obtained from this formula is a positive definite matrix that is satisfied in the standard secant relation. We also show that the largest eigen value of this matrix is not greater than the number of variables of the problem. Then, using this double parameter scaled quasi Newton formula, an explicit formula for calculating the step length in the steepest descent method is presented and therefore, this method does not require the use of approximate methods for calculating step length. The numerical results obtained from the implementation of the algorithm in MATLAB software environment are presented for some optimization problems. These results show the efficiency of the proposed method in comparison with other existing methods.

Newton method is one of the most famous numerical methods among the Line search methods to minimize functions. It is well known that the search direction and step length play important roles in this class of methods to solve optimization problems. In this investigation, a new modi cation of the Newton method to solve uncon-strained optimization problems is presented. The significant merit of the proposed method is that the step length  k at each iteration is equal to 1. Additionally, the convergence analysis for this iterative algorithm is established under suitable conditions. Some illustrative examples are provided to show the validity and applicability of the presented method and a comparison is made with several other existing methods.

Purpose: Users of different discipLines use specific search methods to get the information they need. Knowledge of these methods can help information professionals in designing and increasing accuracy of information retrieval systems. The field of music is not an exception. This study has investigated methods of searching music information sources in search engines by postgraduate students in two universities, namely The University of Fine Arts, and The University of Tehran.methods: All  the 94 postgraduate students in both universities completed a questionnaire. Their fields of study included composition, Iranian music, world music, and musicology (ethnomusicology). The questionnaire was researcher made. Descriptive and inferential statistics techniques were carried out for analysis of data using SPSS software (version 23) and Excel 2013 program.Findings: The students had musical skills such as reading musical notes, knowledge of instruments, knowledge of singers, and knowledge of musical styles, playing instruments at professional levels as well as singing skill at a beginner level. Also, students used general and specialized search engines for music scores, track and song titles, artist names, and album titles. They search in the search engines by exact phrase, specific names and playing music contents, and select retrieved resources according to the credibility, quality of audio files, ease of search and use, music files in mp3 format, and the like.Conclusion: No relationship was found between the level of learning and the use of specialized content search components, space, strategies, resources used, and reasons for selecting sources.