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The university course timetabling problem (UCTP) is a combinatorial optimization problem, in which a set of events has to be scheduled into time slots and located into suitable rooms. The design of course timetables for academic institutions is a very difficult task because it is an NP-hard problem. This paper investigates genetic algorithms (GAs) with a guided search strategy and local search (LS)...
Because traditional approaches for solving the simultaneous localization and map building (SLAM) problem have the limitation of computational complexity, imprecision of filter algorithm and fragile data association, soft computing technique has been used to solve the problem. In this paper, we reviewed the state of the art of the application of evolutionary algorithm, fuzzy logic and neural networks...
We say an algorithm on n × n matrices with entries in [-M, M] (or n-node graphs with edge weights from [-M, M]) is truly subcubic if it runs in O(n3-δ - poly(log M)) time for some δ > 0. We define a notion of subcubic reducibility, and show that many important problems on graphs and matrices solvable in O(n3) time are equivalent under subcubic reductions. Namely, the following weighted problems...
We give sub linear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclosing balls. Our algorithms can be extended to some kernelized versions of these problems, such as SVDD, hard margin SVM, and L2-SVM, for which sub linear-time algorithms were not known before. These new algorithms use a combination...
It has been shown by Indyk and Sidiropoulos that any graph of genus g > 0 can be stochastically embedded into a distribution over planar graphs with distortion 2O(g). This bound was later improved to O(g2) by Borradaile, Lee and Sidiropoulos. We give an embedding with distortion O(log g), which is asymptotically optimal. Apart from the improved distortion, another advantage of our embedding is...
In this paper we introduce a new cardinality constraint: Ordered Distribute. Given a set of variables, this constraint limits for each value v the number of times v or any value greater than v is taken. It extends the global cardinality constraint, that constrains only the number of times a value v is taken by a set of variables and does not consider at the same time the occurrences of all the values...
The notion of vertex sparsification (in particular cut-sparsification) is introduced in, where it was shown that for any graph G = (V, E) and any subset of k terminals K ⊂ V, there is a polynomial time algorithm to construct a graph H = (K, EH) on just the terminal set so that simultaneously for all cuts (A,K-A), the value of the minimum cut in G separating A from K-A is approximately the same as...
In this paper, the time-delay estimation problem is studied for multiple-input single-output (MISO) systems. First, a theoretical analysis is carried out by deriving the Cramer-Rao lower bound (CRLB) for time-delay estimation in a MISO system. Then, the maximum likelihood (ML) estimator for the time-delay parameter is obtained, which results in a complex optimization problem in general. In order to...
This paper presents an efficient and fair uplink resource allocation algorithm in multicarrier based cognitive radio systems. The proposed resource allocation is divided into two steps. The subcarriers to user assignment is first performed and then the power is allocated to the different subcarriers. The subcarriers are allocated based on the channel quality, amount of interference imposed to the...
Wireless spectrum is a limited and valuable resource for communications. However, wireless spectrum is known to be underutilized in spacial, temporal, and spectral domains. The dynamic spectrum access (DSA) of cognitive radio networks provides the capability to improve the spectrum efficiency by allowing secondary users to access the spectrum opportunistically without interfering primary users. The...
Currently, community detection has led to a huge interest in data analysis on real-world networks. However, the high computationally demanding of most community detection algorithms limits their applications. In this paper, we propose a heuristic algorithm to extract the community structure in large networks based on local community attractive force optimization whose time complexity is near linear...
To find MST (Minimum Spanning Trees) in complete graph is a classical problem in operation research having network design as an important application. It is possible to solve MST problem efficiently, but its Biobjective versions are NP hard. In this paper, we present a comparison of two encoding schemes for representing tree in Biobjective optimization scenario. The three different instances of Biobjective...
When a stream application that demands real-time processing over continuous data streams is running on a network-on-chip (NoC)-based multiprocessor system-on-chip (MPSoC), two types of deadlocks may occur: (i) the routing-dependent deadlocks, and (ii) the message-dependent deadlocks. In this paper, we focus on the request-request type message-dependent deadlocks, the most devastating deadlocks in...
Wireless sensor networks consist of various sensor nodes which operate in a memory, energy and bandwidth constrained environment. Target tracking is an important application in wireless sensor networks and in this paper we propose an energy aware target tracking (EATT) algorithm. Energy efficiency is obtained due to the novel concept of tracking being performed in a collaborative manner by different...
One of the key challenges in sensor networks is the extraction of trusted and relevant information by fusing data from a multitude of heterogeneous, distinct, but possibly unreliable or irrelevant sensors. Recovering the desirable view of the environment from the maximum number of dependable sensors while specifying the unreliable ones is an issue of paramount importance for active sensing and robust...
Supporting high-performance computing pipelines in wide-area networks is crucial to enabling large-scale distributed scientific applications that require minimizing end-to-end delay for fast user interaction or maximizing frame rate for smooth data flow. We formulate and categorize the linear pipeline configuration problems into six classes with two mapping objectives, i.e. minimum end-to-end delay...
The main objective of sensor deployment problem in Wireless Sensor Network (WSN) is to use minimum number of sensor nodes with given sensing range that can cover any target in the coverage area to monitor the environment. The optimal sensor deployment enables accurate sensing information on target behavior with minimum sensing range and number of sensor nodes. The target coverage terrain in a locality...
All areas relating to telecommunications, electricity distribution, and gas pipeline require Topological optimization. It also has a major importance in the computer communication industry, when considering network reliability. In this paper, we have used GA with specialized encoding, initialization, local search operators with specially designed crossover operator called alternating crossover [21]...
In this paper the concepts of selective partial updates (SPU) and selective regressors (SR) in the affine projection (AP) adaptive filtering algorithm are combined and the family of affine projection algorithms with SPU and SR features are established. These algorithms are computationally efficient. We demonstrate the performance of the presented algorithms through simulations.
In this paper we propose an approach for timing verification of systems with deterministic and non-repetitive behavior. The timing specification of such systems is often formulated as a system of min-max temporal constraints. We present an algorithm handling all constraint types described in the literature and based on the linearization of min-max inequalities. Optimization techniques are proposed...
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