Sharif Digital Repository

This paper proposes a hybrid optimization method that combines the power of the harmony search (HS) with the mine blast algorithm (MBA). The resulting mine blast harmony search (MBHS) uses MBA for exploration and HS for exploitation. The HS is inspired by the improvisation process of musicians, while the MBA is derived based on explosion of landmines. The HS used in the hybrid algorithm is an improved version, introducing a new concept for the harmony memory size, while the MBA is modified in terms of its mathematical formulation. Several numerical problems and benchmarks with many design variables and constraints are used to validate MBHS, and the optimization results are compared with... 

Wide-waisted Gaussian beam (GB) expansion and point matching methods are discussed in this study as promising techniques for the expansion of electromagnetic waves into GBs. These methods combined with the GB tracing method provide an appropriate scheme for wave propagation analysis in large-scale problems. Details of the wide-waisted GB expansion and point matching methods are provided, and their accuracy and validity regions are discussed. A combination of the aforementioned expansion and tracing methods is utilised to analyse a simple outdoor high-frequency wave propagation problem. The results are compared to the results of the well-known ray tracing method, showing good agreement  

This paper is devoted to the problem of improving network performance to withstand incidents such as earthquakes, which have long-term adverse-effect upon the networks. A measure of link importance is presented based on consumers' surplus. This measure is then used to define and solve a network improvement problem. Computational complexities are reduced by introducing an approximate measure of link importance which performs almost as good, and hence may be used for solving large scale problems. Several example networks are used to clarify the discussion numerically. © Springer 2005  

We first establish some necessary and sufficient conditions for solvability of fuzzy LR linear systems. We then propose a concept for an approximate solution when a fuzzy LR linear system lacks a solution. Recently, we have proposed an approximate solution for a fuzzy LR linear system under the condition that a corresponding crisp linear system was solvable. Here, we remove this condition by presenting a more general concept of an approximate solution based on a least squares model. We also develop the conditions for the uniqueness of the approximate solution. To compute an approximate solution, we propose an algorithm based on a quadratic programming model with bound constraints on some... 

Recovering low-rank and sparse components from missing observations is an essential problem in various fields. In this paper, we have proposed a method to address the missing low-rank and sparse decomposition problem. We have used the smoothed nuclear norm and the L1 norm to impose the low-rankness and sparsity constraints on the components, respectively. Furthermore, we have suggested a linear modeling for the corrupted observations. The problem has been solved with the aid of alternating minimization. Moreover, some simplifications have been applied to the relations to reduce the computational complexity, which makes the algorithm suitable for large-scale problems. To evaluate the proposed... 

Semi-Supervised Learning (SSL) has become a topic of recent research that effectively addresses the problem of limited labeled data. Many SSL methods have been developed based on the manifold assumption, among them, the Local and Global Consistency (LGC) is a popular method. The problem with most of these algorithms, and in particular with LGC, is the fact that their naive implementations do not scale well to the size of data. Time and memory limitations are the major problems faced in large-scale problems. In this paper, we provide theoretical bounds on gradient descent, and to overcome the aforementioned problems, a new approximate Newton's method is proposed. Moreover, convergence... 

The vehicle routing problem (VRP) is one of the most complicated optimization mathematical models; the school bus routing problem (SBRP) is an important and practical branch of this problem. Because the number of variables and equations is vast, finding the exact solution for this problem under real conditions is difficult; only heuristic and metaheuristic algorithms can be used to solve it. Recently, the ejection chain method (ECM) has been introduced as a heuristic algorithm that efficiently finds a new neighbor solution. In a case study in developing countries, efficiency of several heuristic algorithms including ECM along with one metaheuristic algorithm-tabu search algorithm (TSA)-is... 

This paper presents optimal scheduling in a two-machine flow shop, in which the objective function is to minimize the sum of maximum earliness and tardiness (n/2/P/ETmax). Since this problem tries to minimize earliness and tardiness, the results can be useful for different production systems such as just in time (JIT). This objective function has already been considered for n jobs and m machines, but the proposed algorithms are not efficient to solve large scale problems. In this paper, neighborhood conditions are developed and the dominant set for any optimal solution is determined. The branch-and-bound (B&B) method is used to solve the problem and the proper upper and lower bounds are also...