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One of challenging problems in the domain of web services is the web service composition (i.e the task of composing web services to create new services, capable of fulfilling a need that no single service can satisfy). In real application, there will be a lot of relevant web services for a simple goal, so the search space for such a problem is huge. In this research statement, we show how by extracting some prior knowledge and using simple heuristics, search space and search time can be reduced significantly  

We establish several new results on Marton's inner bound on the capacity region of the general broadcast channel. Inspired by the fact that Marton's coding scheme without superposition coding is optimal in the Gaussian case, we consider the class of binary input degraded broadcast channels with no common message that have the same property. We characterize this class. We also establish new properties of Marton's inner bound that help restrict the search space for computing the Marton sum rate. In particular, we establish an extension of the XOR case of the binary inequality of Nair, Wang, and Geng  

This paper presents a new interpretable fuzzy classification system. Simulated annealing heuristic is employed to effectively investigate the large search space usually associated with classification problem. Here, two criteria are used to evaluate the proposed method. The first criterion is accuracy of extracted fuzzy if-then rules, and the other is comprehensibility of obtained rules. Experiments are performed with some data sets from UCI machine learning repository. Results are compared with several well-known classification algorithms, and show that the proposed approach provides more accurate and interpretable classification system. © 2009 IEEE  

Marton's inner bound is the best known achievable region for a general discrete memoryless broadcast channel. To compute Marton's inner bound one has to solve an optimization problem over a set of joint distributions on the input and auxiliary random variables. The optimizers turn out to be structured in many cases. Finding properties of optimizers not only results in efficient evaluation of the region, but it may also help one to prove factorization of Marton's inner bound (and thus its optimality). The first part of this paper formulates this factorization approach explicitly and states some conjectures and results along this line. The second part of this paper focuses primarily on the... 

Synthesis of the optimum distillation column sequence (DCS), which incorporates a huge search space composed of both conventional and complex arrangements, is a highly complicated combinatorial problem in the field of chemical process design and optimisation. In this study, a novel procedure for the synthesis of optimum DCS proposed by Boozarjomehry et al. [Boozarjomehry et al., Can. J. Chem. Eng. 87, 477-492 (2009)] is expanded to include the complex distillation arrangements. The method is based on evolutionary algorithms, and the total annual cost (TAC) is the main criterion used to screen alternatives. Efficient procedure has been proposed for encoding mechanism to include and classify... 

One of the major challenge and time-consuming work is optimum test data generation to assure software quality. Researchers have proposed several methods over years to generate automatically solution which have different drawbacks. In this paper, we propose Genetic Algorithm (GA) based tester with different parameters to automate the structural-oriented test data generation on the basis of internal program structure. Our proposed fitness function is intended to traverse paths of the program as more as possible. This integration improves the GA performance in search space exploration and exploitation fields with faster convergence. At last, we present some results according to our experiment... 

Workspace of a mechanism is generally defined as the region of space which end-effector of that mechanism can reach. Determination of workspace is an important task in the design of a mechanism. However, for parallel mechanisms, due to the complexity of solving the forward kinematic equations, determination of workspace is much more complicated than for serial mechanisms. In the literature, time-consuming numerical methods, such as point-by-point searching, are usually employed for this purpose. In this paper, an optimization-based algorithm is introduced for the boundary determination of inclusive and constant orientation workspaces of parallel mechanisms. In the proposed algorithm, thanks... 

Synthesis of the optimum conventional (with non-sharp separations) distillation column sequence (DCS) is a challenging problem, in the field of chemical process design and optimization, due to its huge search space and combinatorial nature. In this paper, a novel procedure for the synthesis of optimum Conventional Distillation Column Sequence is proposed. The proposed method is based on evolutionary algorithms. The main criterion used to screen alternative DCS's is the Total Annual Cost (TAC). In order to estimate the TAC of each DCS alternative all columns that exist in the DCS are designed using short-cut methods. The performance of the proposed method and other alternatives are compared... 

Given a graph, the sparsest cut problem asks for a subset of vertices whose edge expansion (the normalized cut given by the subset) is minimized. In this paper, we study a generalization of this problem seeking for k disjoint subsets of vertices (clusters) whose edge expansions are small and furthermore, the number of vertices that remained in the exterior of the subsets (outliers) is also small. It is proved in Daneshgar et al. (2012) that this problem is NP-hard for trees. Here, we prove that it can be solved in polynomial time for all weighted trees, provided that the search space is restricted to subsets inducing connected subgraphs. The additional constraint has justifications in... 

Optimizing highway alignment requires a versatile set of cost functions and an efficient search method to achieve the best design. Because of numerous highway design considerations, this issue is classified as a constrained problem. Moreover, because of the infinite number of possible solutions for the problem and the continuous search space, highway alignment optimization is a complex problem. In this study, a customized particle swarm optimization algorithm was used to search for a near-optimal highway alignment, which is a compound of several tangents, consisting of circular (for horizontal design) and parabolic (for vertical alignment) curves. The selected highway alignment should meet... 

In large population Speaker Identification (SI), computation time has become one of the most important issues in recent real time systems. Test computation time depends on the cost of likelihood computation between test features and registered speaker models. For real time application of speaker identification, system must identify an unknown speaker quickly. Hence the conventional SI methods cannot be used. In this paper, we propose a two-step method that utilizes two different identification methods. In the first step we use Nearest Neighbor method to decrease the search space. In the second step we use GMM-based SI methods to specify the target speaker. We achieved 3.5× speed-ups without... 

A new hybrid approach for dynamic optimization problems with continuous search spaces is presented. The proposed approach hybridizes efficient features of the particle swarm optimization in tracking dynamic changes with a new evolutionary procedure. In the proposed dynamic hybrid PSO (DHPSO) algorithm, the swarm size is varied in a self-regulatory manner. Inspired from the microbial life, the particles can reproduce infants and the old ones die. The infants are especially reproduced by high potential particles and located near the local optimum points, using the quadratic interpolation method. The algorithm is adapted to perform in continuous search spaces, utilizing continuous movement of... 

The key element of a spoken dialogue system is a spoken language understanding (SLU) unit. Hidden Vector State (HVS) is one of the most popular statistical approaches employed to implement the SLU unit. This paper presents a two-step approach for Persian language understanding. First, a goal detector is used to identify the main goal of the input utterance. Second, after restricting the search space for semantic tagging, an extended hidden vector state (EHVS) parser is used to extract the remaining semantics in each subspace. This will mainly improve the performance of semantic tagger, while reducing the model complexity and training time. Moreover, the need for large amount of data will be... 

Due to fast growth of wireless mobile networks, video transmission over wireless media has been widely studied. As wireless networks are error prone, there is a high possibility of loss in sent packets. Since time limitations in real-time video applications should be met, the delay-related to resending packets is not acceptable and the error should to be concealed at receiver side. With respect to different concealment methods, two new methods for temporal error concealment are proposed. In the first method, an optimized set of motion vectors is formed using motion vectors in surrounding blocks of the lost macroblock, and then this set is searched for the best motion vector. For extending... 

Motivated by the decompositions of sphere and QR-based methods, in this paper we present an extremely fast maximum-likelihood (ML) detection approach for quasi-orthogonal space-time block code (QOSTBC). The proposed algorithm with a relatively simple design exploits structure of quadrature amplitude modulation (QAM) constellations to achieve its goal and can be extended to any arbitrary constellation. Our decoder utilizes a new decomposition technique for ML metric which divides the metric into independent positive parts and a positive interference part. Search spaces of symbols are substantially reduced by employing the independent parts and statistics of noise. Symbols within the search... 

The main core of HMM-based speech recognition systems is Viterbi algorithm. Viterbi algorithm uses dynamic programming to find out the best alignment between the input speech and a given speech model. In this paper, dynamic programming is replaced by a search method which is based on particle swarm optimization algorithm. The major idea is focused on generating an initial population of segmentation vectors in the solution search space and improving the location of segments by an updating algorithm. Several methods are introduced and evaluated for the representation of particles and their corresponding movement structures. In addition, two segmentation strategies are explored. The first... 

A new hybrid optimization method, combining Continuous Ant Colony System (CACS) and Tabu Search (TS) is proposed for minimization of continuous multi-minima functions. The new algorithm incorporates the concepts of promising list, tabu list and tabu balls from TS into the framework of CACS. This enables the resultant algorithm to avoid bad regions and to be guided toward the areas more likely to contain the global minimum. New strategies are proposed to dynamically tune the radius of the tabu balls during the execution and also to handle the variable correlations. The promising list is also used to update the pheromone distribution over the search space. The parameters of the new method are... 

The main core of HMM-based speech recognition systems is the Viterbi Algorithm. Viterbi is performed using dynamic programming to find out the best alignment between input speech and given speech model. In this paper, dynamic programming is replaced by a search method which is based on particle swarm optimization algorithm. The major idea is focused on generating an initial population of segmentation vectors in the solution search space and improving the location of segments by an updating algorithm. Two methods are introduced for representation of each particle and movement structure. The results show that the effect of these factors is noticeable in finding the global optimum while... 

Due to special constraints in peer-to-peer (P2P) networks (such as bandwidth limitation) and because of their highly dynamic characteristics, a single node cannot provide a reliable multimedia stream to the receivers. Several multi-sender algorithms are proposed to reliably deliver a media stream to the receiver through the intrinsically unreliable P2P networks. Based on upload bandwidths and availability of peers as well as the bandwidths of the links connecting the senders and the receiver, PROMISE selects a set of active senders to maximize the expected bit-rate delivered to the receiver. By careful investigation of PROMISE, in this paper, we present why and how it deviates from finding... 

In this paper, we use simulated annealing heuristics for constructing an intrusion detection system (IDS). The proposed IDS combines the learning ability of simulated annealing heuristics with the approximate reasoning method of fuzzy systems. The use of simulated annealing is an effort to effectively explore the large search space related to intrusion detection problems, and find the optimum set of fuzzy if-then rules. The aim of this paper is to present the capability of simulated annealing based fuzzy system to deal with intrusion detection classification problem as a new real-world application area. Experiments were performed with KDD-Cup99 intrusion detection benchmark data set. © 2008...