Sharif Digital Repository

The objective of the dynamic economic dispatch (DED) problem is to schedule power generation for the online units for a given time horizon economically, satisfying various operational constraints. Due to the effect of valve-point effects and prohibited operating zones (POZs) in the generating units cost functions, DED problem is a highly non-linear and non-convex optimization problem. The DED problem even may be more complicated if transmission losses and ramp-rate constraints are taken into account. This paper presents a novel and heuristic algorithm to solve DED problem of generating units, by employing time varying acceleration coefficients iteration particle swarm optimization... 

This paper focuses on the flow shop sequence dependent group scheduling (FSDGS) problem with minimisation of total completion time as the criterion (Fm|f mls, prmu, S plk|ΣC j). The research problem is formulated in form of two different mixed integer linear programming (MILP) models. Comparing with the latest MILP model for the proposed problem in the literature, the complexity size of the proposed models are significantly reduced. One of the proposed mathematical models is so effective that even medium-sized instances (problems up to 60 jobs in all groups) are solved to optimality in a reasonable amount of time. Moreover, a metaheuristic hybridising genetic and simulated annealing... 

We present an optimal solution procedure for minimizing total weighted resource tardiness penalty costs in the resource-constrained project scheduling problem. In this problem, we assume the constrained renewable resources are limited to very expensive equipments and machines that are used in other projects and are not available in all periods of time of a project. In other words, for each resource, there is a dictated ready date as well as a due date such that no resource can be available before its ready date but the resources are permitted to be used after their due dates by paying penalty cost depending on the resource type. We also assume that only one unit of each resource type is... 

Aximum coverage location problem is considered in this study. Extension of this problem is investigated for situations that coverage areas are elliptical; these ellipses can locate anywhere on the plane with any angle. Mixed integer nonlinear programming (MINLP) is applied for formulation. This problem can be used in many practical situations such as locating wireless transmitter towers. A heuristic algorithm named MCLPEA for solving this problem was designed. This algorithm can produce very good results in efficient running time. Finally, the comparison of the results for this study was carried done  

This paper investigates permutation flow shop scheduling problems with sequencedependent setup times with minimizing the number of tardy jobs as criterion (F m|prmu, S ijk|σU j). Since the proposed research problem has been proven to be NP-hard, three different meta heuristic algorithms based on tabu search (TS) has been proposed to solve the problem. These three algorithms are different based on their tabu list characteristics. In order to evaluate the performance of the proposed TS algorithms, test problems in different ranges are generated to find the best algorithm. The comparison shows that the TS algorithm which its tabu list keeps track of the slots that the jobs are assigned has a... 

This paper is aimed at investigating some computational aspects of different isoperimetric problems on weighted trees. In this regard, we consider different connectivity parameters called minimum normalized cuts/isoperimetric numbers defined through taking the minimum of the maximum or the mean of the normalized outgoing flows from a set of subdomains of vertices, where these subdomains constitute a partition/subpartition. We show that the decision problem for the case of taking k-partitions and the maximum (called the max normalized cut problem NCPM), and the other two decision problems for the mean version (referred to as IPPm and NCPm) are NP-complete problems for weighted trees. On the... 

Automatic image annotation is a challenging problem in the field of image retrieval. Dealing with large databases makes the annotation problem more difficult and therefore an effective approach is needed to manage such databases. In this work, an annotation system has been developed which considers images in separate categories and constructs a profiling model for each category. To describe an image, we propose a new feature extraction method based on color and texture information that describes image content using discrete distribution signatures. Image signatures of one category are partitioned using spectral clustering and a prototype is determined for each cluster by solving an... 

In this study, the nonlinear vibrations analysis of an inclined pinned-pinned self-weight Timoshenko beam made of linear, homogenous and isotropic material with a constant cross section and finite length subjected to a traveling mass/force with constant velocity is investigated. The nonlinear coupled partial differential equations of motion for the rotation of warped cross section, longitudinal and transverse displacements are derived using the Hamilton's principle. These nonlinear coupled PDEs are solved by applying the Galerkin's method to obtain dynamic responses of the beam. The dynamic magnification factor and normalized time histories of mid-point of the beam are obtained for various... 

Since that heuristic state space planners have been very successful in classical planning, this approach is currently the most popular strategy in dealing with temporal planning, too. However, all current state-space temporal planners use a search method known as decision epoch planning, which is not complete for problems with required concurrency. In theory, this flaw can be overcome by employing another search method, called temporally lifted progression planning. In this paper, we show that there are two major problems which, if not tackled properly, can cause the latter method to be very inefficient in practice. The first problem is dealing with the remarkably large state space of... 

The maximal covering location problem (MCLP) is a challenging problem with numerous applications in practice. Previous publications in the area of MCLP proposed models and presented solution methodologies to solve this problem with up to 900 nodes. Due to the fact that in real-life applications, the number of nodes could be much higher, this paper presents a customized Genetic Algorithm (GA) to solve MCLP instances, with up to 2500 nodes. Results show that the proposed approach is capable of solving problems with a fair amount of exactness. In order to fine-tune the algorithm, Tukey's Least Significant Difference (LSD) tests are employed on a set of test problems  

Computational intelligence (CI) as an offshoot of artificial intelligence (AI), is becoming more and more widespread nowadays for solving different engineering problems. Especially by embracing Swarm Intelligence techniques such as ant colony optimization (ACO), CI is known as a good alternative to classical AI for dealing with practical problems which are not easy to solve by traditional methods. Besides, electricity load forecasting is one of the most important concerns of power systems, consequently; developing intelligent methods in order to perform accurate forecasts is vital for such systems. This study presents a hybrid CI methodology (called ACO-GA) by integration of ant colony... 

The mathematical techniques of decision making are among the most valuable outcomes of this research activity, which is generally referred to as realization in the operations, operational research or quantitative methods of decision making. Over time, with the increase in the complexity and the variety of decision making problems, the methods of decision making become more varied and will have more capability of problem solving. Multi-Criteria Decision Making (MCDM) is a collection of methodologies to compare, select, or rank multiple alternatives that involve incommensurate attributes. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is a multiple criteria... 

A Hub Location Problem (HLP) deals with finding the locations of hub facilities and assignment of demand nodes to established facilities. Hubs play a central role in many networks such as telecommunication networks and their unavailability may lead to network breakdown or poor service levels. An objective in design of a hub-and-spoke network is maximization of reliability to transfer flows. This paper puts forward design of a reliable single-allocation hub-and-spoke network using an interactive fuzzy goal programming. To model and solve the problem, a fuzzy goal programming approach was developed for design of network in an interactive manner between decision maker and the model. To validate... 

In general, decomposition methods can facilitate the process of solving sophisticated and heterogonous problems in the area of software development and engineering. These approaches are assisting to decompose problems based on different disciplines, characteristics and functionalities that is results into increasing the computational efficiency (e.g. parallel processing/computing) and accelerate the software changing process, software modifications and error tracking. Essentially, these approaches contribute to the degree of modularity to decompose a complex problem into different sub-problems and to focus on local objectives. There are different approaches that are used to decompose a... 

The flowshop sequence dependent group scheduling problem with minimization of makespan as the objective (F m |fmls, S plk, prmu|C max ) is considered in this paper. It is assumed that several groups with different number of jobs are assigned to a flow shop cell that has m machines. The goal is to find the best sequence of processing the jobs in each group and the groups themselves with minimization of makespan as the objective. A mathematical model for the research problem is developed in this paper. As the research problem is shown to be NP-hard, a hybrid ant colony optimization (HACO) algorithm is developed to solve the problem. A lower bounding technique based on relaxing a few... 

Periodic solutions and their existence are one of the most important subjects in dynamical systems. Fractional order systems like integer ones are no exception to this rule. Tavazoei and Haeri (2009) have shown that a time-invariant fractional order system does not have any periodic solution. In this article, this claim has been investigated and it is shown that although in any finite interval of time the solutions do not show any periodic behavior, when the steady state responses of fractional order systems are considered, periodic orbits can be detected  

This study presents a motion planning algorithm to generate a feasible periodic solution for a hybrid system describing running by a three-dimensional (3-D), three-link, three-actuator, monopedal robot. In order to obtain a symmetric running gait along a straight line, the hybrid system consists of two stance phases and two flight phases. The motion planning algorithm is developed on the basis of a finite-dimensional optimisation problem with equality and inequality constraints. By extending the concept of hybrid zero dynamics to running, the authors propose a time-invariant control scheme that is employed at two levels to locally exponentially stabilise the generated periodic solution for... 

We study permutation betting markets, introduced by Chen et al. (Proceedings of the ACM Conference on Electronic Commerce, 2007). For these markets, we consider subset bettings in which each trader can bet on a subset of candidates ending up in a subset of positions. We consider the revenue maximization problem for the auctioneer in two main frameworks: the risk-free revenue maximization (studied in Chen et al., Proceedings of the ACM Conference on Electronic Commerce, 2007), and the probabilistic revenue maximization. We also explore the use of some certain knowledge or extra information about the possible outcomes of the market. We first show that finding the optimal revenue in the... 

For a set of n disjoint line segments S in R2, the visibility counting problem (VCP) is to preprocess S such that the number of visible segments in S from a query point p can be computed quickly. For this configuration, the visibility testing problem (VTP) is to test whether p sees a fixed segment s. These problems can be solved in logarithmic query time by using O(n4) preprocessing time and space. In this paper, we approximately solve this problem using quadratic preprocessing time and space. Our methods are superior to current approximation algorithms in terms of both approximation factor and preprocessing cost. In this paper, we propose a 2-approximation algorithm for the VCP using at... 

Constrained clustering methods (that usually use must-link and/or cannot-link constraints) have been received much attention in the last decade. Recently, kernel adaptation or kernel learning has been considered as a powerful approach for constrained clustering. However, these methods usually either allow only special forms of kernels or learn non-parametric kernel matrices and scale very poorly. Therefore, they either learn a metric that has low flexibility or are applicable only on small data sets due to their high computational complexity. In this paper, we propose a more efficient non-linear metric learning method that learns a low-rank kernel matrix from must-link and cannot-link...