Journal of Optimization The latest articles from Hindawi Publishing Corporation © 2014 , Hindawi Publishing Corporation . All rights reserved. Equal Angle Distribution of Polling Directions in Direct-Search Methods Sun, 20 Jul 2014 11:18:47 +0000 The purpose of this paper is twofold: first, to introduce deterministic strategies for directional direct-search methods, including new instances of the mesh adaptive direct-search (MADS) and the generating set search (GSS) class of algorithms, which utilize a nice distribution of PoLL directions when compared to other strategies, and second, to introduce variants of each algorithm which utilize a minimal positive basis at each step. The strategies base their PoLL directions on the use of the QR decomposition to obtain an orthogonal set of directions or on using the equal angular directions from a regular simplex centered at the origin with vertices on the unit sphere. Test results are presented on a set of smooth, nonsmooth, unconstrained, and constrained problems that give comparisons between the various implementations of these directional direct-search methods. Benjamin Van Dyke Copyright © 2014 Benjamin Van Dyke. All rights reserved. An Optimization-Based Approach to Calculate Confidence Interval on Mean Value with Interval Data Sun, 13 Jul 2014 07:23:26 +0000 In this paper, we propose a methodology for construction of confidence interval on mean values with interval data for input variable in uncertainty analysis and design optimization problems. The construction of confidence interval with interval data is known as a combinatorial optimization problem. Finding confidence bounds on the mean with interval data has been generally considered an NP hard problem, because it includes a search among the combinations of multiple values of the variables, including interval endpoints. In this paper, we present efficient algorithms based on continuous optimization to find the confidence interval on mean values with interval data. With numerical experimentation, we show that the proposed confidence bound algorithms are scalable in polynomial time with respect to increasing number of intervals. Several sets of interval data with different numbers of intervals and type of overlap are presented to demonstrate the proposed methods. As against the current practice for the design optimization with interval data that typically implements the constraints on interval variables through the computation of bounds on mean values from the sampled data, the proposed approach of construction of confidence interval enables more complete implementation of design optimization under interval uncertainty. Kais Zaman and Saraf Anika Kritee Copyright © 2014 Kais Zaman and Saraf Anika Kritee. All rights reserved. Beamforming with Reduced Complexity in MIMO Cooperative Cognitive Radio Networks Tue, 06 May 2014 12:11:27 +0000 An approach for beamforming with reduced complexity in MIMO cooperative cognitive radio networks (MIMO-CCRN) is presented. Specifically, a suboptimal approach with reduced complexity is proposed to jointly determine the transmit beamforming (TB) and cooperative beamforming (CB) weight vectors along with antenna subset selection in MIMO-CCRN. Two multiantenna secondary users (SU) constitute the desired link, one acting as transmitter (SU TX) and the other as receiver (SU RX) and they coexist with single-antenna primary and secondary users. Some of single antenna secondary users are recruited by desired link as cooperative relay. The maximization of the achievable rates in the desired link is the objective of this work, provided to interference constraints on the primary users are not violated. The objective is achieved by exploiting transmit beamforming at SU TX, cooperation of some secondary users, and cooperative beamforming. Meanwhile, the costs associated with RF chains at the radio front end at SU RX are reduced. Through simulations, it is shown that better performance in the desired link is attained, as a result of cooperation of SUs. Mehdi Ghamari Adian Copyright © 2014 Mehdi Ghamari Adian. All rights reserved. Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems Wed, 19 Feb 2014 14:20:15 +0000 A polymorphic uncertain linear programming (PULP) model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems. Xinbo Zhang, Feng Zhang, Xiaohong Chen, and Zhong Wan Copyright © 2014 Xinbo Zhang et al. All rights reserved. A Nonmonotone Adaptive Trust Region Method Based on Conic Model for Unconstrained Optimization Mon, 27 Jan 2014 07:57:11 +0000 We propose a nonmonotone adaptive trust region method for unconstrained optimization problems which combines a conic model and a new update rule for adjusting the trust region radius. Unlike the traditional adaptive trust region methods, the subproblem of the new method is the conic minimization subproblem. Moreover, at each iteration, we use the last and the current iterative information to define a suitable initial trust region radius. The global and superlinear convergence properties of the proposed method are established under reasonable conditions. Numerical results show that the new method is efficient and attractive for unconstrained optimization problems. Zhaocheng Cui Copyright © 2014 Zhaocheng Cui. All rights reserved. Determining Bounds on Assumption Errors in Operational Analysis Sun, 12 Jan 2014 00:00:00 +0000 The technique of operational analysis (OA) is used in the study of systems performance, mainly for estimating mean values of various measures of interest, such as, number of jobs at a device and response times. The basic principles of operational analysis allow errors in assumptions to be quantified over a time period. The assumptions which are used to derive the operational analysis relationships are studied. Using Karush-Kuhn-Tucker (KKT) conditions bounds on error measures of these OA relationships are found. Examples of these bounds are used for representative performance measures to show limits on the difference between true performance values and those estimated by operational analysis relationships. A technique for finding tolerance limits on the bounds is demonstrated with a simulation example. Neal M. Bengtson Copyright © 2014 Neal M. Bengtson. All rights reserved. Memetic Algorithm with Local Search as Modified Swine Influenza Model-Based Optimization and Its Use in ECG Filtering Thu, 02 Jan 2014 11:16:46 +0000 The Swine Influenza Model Based Optimization (SIMBO) family is a newly introduced speedy optimization technique having the adaptive features in its mechanism. In this paper, the authors modified the SIMBO to make the algorithm further quicker. As the SIMBO family is faster, it is a better option for searching the basin. Thus, it is utilized in local searches in developing the proposed memetic algorithms (MAs). The MA has a faster speed compared to SIMBO with the balance in exploration and exploitation. So, MAs have small tradeoffs in convergence velocity for comprehensively optimizing the numerical standard benchmark test bed having functions with different properties. The utilization of SIMBO in the local searching is inherently the exploitation of better characteristics of the algorithms employed for the hybridization. The developed MA is applied to eliminate the power line interference (PLI) from the biomedical signal ECG with the use of adaptive filter whose weights are optimized by the MA. The inference signal required for adaptive filter is obtained using the selective reconstruction of ECG from the intrinsic mode functions (IMFs) of empirical mode decomposition (EMD). Devidas G. Jadhav, Shyam S. Pattnaik, and Sanjoy Das Copyright © 2014 Devidas G. Jadhav et al. All rights reserved. Nondifferentiable Minimax Programming Problems in Complex Spaces Involving Generalized Convex Functions Sun, 22 Dec 2013 10:14:20 +0000 We start our discussion with a class of nondifferentiable minimax programming problems in complex space and establish sufficient optimality conditions under generalized convexity assumptions. Furthermore, we derive weak, strong, and strict converse duality theorems for the two types of dual models in order to prove that the primal and dual problems will have no duality gap under the framework of generalized convexity for complex functions. Anurag Jayswal, Ashish Kumar Prasad, and Krishna Kummari Copyright © 2013 Anurag Jayswal et al. All rights reserved. Application of Fuzzy DEMATEL in Risks Evaluation of Knowledge-Based Networks Mon, 16 Dec 2013 15:41:07 +0000 Developing new products has received much attention within the last decades. This issue can be highlighted for strategic innovations, in particular. Recently, knowledge-based networks have been introduced in order to facilitate the affair of transforming knowledge into commercial products which can be regarded as a set of research centers, universities, knowledge intermediaries, customers, and so forth. However, there is a wide range of risk factors that are liable to affect the chain performance. Hence, this paper aims to consider the most influencing criteria that can play a more significant role in achievements of such networks. To do so, DEMATEL has been applied to take the relationships between the risk factors into account. Moreover, fuzzy set theory has been utilized in order to deal with the linguistic variables. Finally, the most important factors are identified and their relations are determined. M. Abbasi, R. Hosnavi, and B. Tabrizi Copyright © 2013 M. Abbasi et al. All rights reserved. Double Flight-Modes Particle Swarm Optimization Mon, 16 Dec 2013 08:49:06 +0000 Getting inspiration from the real birds in flight, we propose a new particle swarm optimization algorithm that we call the double flight modes particle swarm optimization (DMPSO) in this paper. In the DMPSO, each bird (particle) can use both rotational flight mode and nonrotational flight mode to fly, while it is searching for food in its search space. There is a King in the swarm of birds, and the King controls each bird’s flight behavior in accordance with certain rules all the time. Experiments were conducted on benchmark functions such as Schwefel, Rastrigin, Ackley, Step, Griewank, and Sphere. The experimental results show that the DMPSO not only has marked advantage of global convergence property but also can effectively avoid the premature convergence problem and has good performance in solving the complex and high-dimensional optimization problems. Wang Yong, Li Jing-yang, and Li Chun-lei Copyright © 2013 Wang Yong et al. All rights reserved. Dynamic Optimization Technique for Distribution of Goods with Stochastic Shortages Sun, 15 Dec 2013 14:52:15 +0000 This work considers the distribution of goods with stochastic shortages from factories to stores. It is assumed that in the process of shipping the goods to various stores, some proportion of the goods will be damaged (which will lead to shortage of goods in transit). The cost of the damaged goods is added to the cost of the shipment. A proportion of the total expected cost of the shortage goods is assumed to be recovered and should be deducted from the total cost of the shipment. In order to determine the minimum transportation costs for the operation, we adopt dynamic optimization principles. The optimal transportation cost and optimal control policies of shipping the goods from factories to stores were obtained. We find that the optimal costs of the goods recovered could be determined. It was further found that the optimum costs of distributing the goods with minimum and maximum error bounds coincide only at infinity. Charles I. Nkeki Copyright © 2013 Charles I. Nkeki. All rights reserved. Quasiconvex Semidefinite Minimization Problem Thu, 12 Dec 2013 15:39:03 +0000 We introduce so-called semidefinite quasiconvex minimization problem. We derive new global optimality conditions for the above problem. Based on the global optimality conditions, we construct an algorithm which generates a sequence of local minimizers which converge to a global solution. R. Enkhbat and T. Bayartugs Copyright © 2013 R. Enkhbat and T. Bayartugs. All rights reserved. Multiobjective Optimization Using Cross-Entropy Approach Tue, 10 Dec 2013 12:25:02 +0000 A new approach for multiobjective optimization is proposed in this paper. The method based on the cross-entropy method for single objective optimization (SO) is adapted to MO optimization by defining an adequate sorting criterion for selecting the best candidates samples. The selection is made by the nondominated sorting concept and crowding distance operator. The effectiveness of the approach is tested on several academic problems (e.g., Schaffer, Fonseca, Fleming, etc.). Its performances are compared with those of other multiobjective algorithms. Simulation results and comparisons based on several performance metrics demonstrate the effectiveness of the proposed method. Karim Sebaa, Abdelhalim Tlemçani, Mounir Bouhedda, and Noureddine Henini Copyright © 2013 Karim Sebaa et al. All rights reserved. Spectrum of Permanent’s Values and Its Extremal Magnitudes in and Sun, 17 Nov 2013 14:01:21 +0000 Let denote the class of square matrices containing in each row and in each column exactly 1’s. The minimal value of , for which the behavior of the permanent in is not quite studied, is . We give a simple algorithm for calculation of upper magnitudes of permanent in and consider some extremal problems in a generalized class , the matrices of which contain in each row and in each column nonzero elements , , and and zeros. Vladimir Shevelev Copyright © 2013 Vladimir Shevelev. All rights reserved. Soft Computing Techniques for Mutual Coupling Reduction in Metamaterial Antenna Array Wed, 06 Nov 2013 14:51:25 +0000 Application of soft computing techniques for various metamaterial designs and optimizations is an emerging field in the microwave regime. In this paper, a global optimization technique, namely, particle swarm optimization (PSO), is used for the design and optimization of a square split ring resonator (SSRR) having a resonant frequency of 2.4 GHz. The PSO optimizer yields the structural parameters, which is further simulated and validated with the optimized value. This optimized structure results in the mutual coupling reduction in a microstrip antenna array designed for wireless application. Balamati Choudhury, Sangeetha Manickam, and R. M. Jha Copyright © 2013 Balamati Choudhury et al. All rights reserved. An Optimal Method for Developing Global Supply Chain Management System Sun, 20 Oct 2013 11:35:39 +0000 Owing to the transparency in supply chains, enhancing competitiveness of industries becomes a vital factor. Therefore, many developing countries look for a possible method to save costs. In this point of view, this study deals with the complicated liberalization policies in the global supply chain management system and proposes a mathematical model via the flow-control constraints, which are utilized to cope with the bonded warehouses for obtaining maximal profits. Numerical experiments illustrate that the proposed model can be effectively solved to obtain the optimal profits in the global supply chain environment. Hao-Chun Lu and Yao-Huei Huang Copyright © 2013 Hao-Chun Lu and Yao-Huei Huang. All rights reserved. PRO: A Novel Approach to Precision and Reliability Optimization Based Dominant Point Detection Thu, 26 Sep 2013 08:07:12 +0000 A novel method that uses both the local and the global nature of fit for dominant point detection is proposed. Most other methods use local fit to detect dominant points. The proposed method uses simple metrics like precision (local nature of fit) and reliability (global nature of fit) as the optimization goals for detecting the dominant points. Depending on the desired level of fitting (very fine or crude), the threshold for precision and reliability can be chosen in a very simple manner. Extensive comparison of various line fitting algorithms based on metrics such as precision, reliability, figure of merit, integral square error, and dimensionality reduction is benchmarked on publicly available and widely used datasets (Caltech 101, Caltech 256, and Pascal (2007, 2008, 2009, 2010) datasets) comprising 102628 images. Such work is especially useful for segmentation, shape representation, activity recognition, and robust edge feature extraction in object detection and recognition problems. Dilip K. Prasad Copyright © 2013 Dilip K. Prasad. All rights reserved. Optimal Multiplicative Generalized Linear Search Plan for a Discrete Random Walker Tue, 30 Jul 2013 11:57:57 +0000 This paper formulates a search model that gives the optimal search plan for the problem of finding a discrete random walk target in minimum time. The target moves through one of n-disjoint real lines in : we have n-searchers starting the searching process for the target from any point rather than the origin. We …find the conditions that make the expected value of the fi…rst meeting time between one of the searchers and the target fi…nite. Furthermore, we show the existence of the optimal search plan that minimizes the expected value of the fi…rst meeting time and fi…nd it. The effectiveness of this model is illustrated using numerical example. Abd-Elmoneim Anwar Mohamed and Mohamed Abd Allah El-Hadidy Copyright © 2013 Abd-Elmoneim Anwar Mohamed and Mohamed Abd Allah El-Hadidy. All rights reserved. Optimization of Balking and Reneging Queue with Vacation Interruption under -Policy Thu, 27 Jun 2013 08:34:51 +0000 This paper analyzes a finite buffer multiple working vacations queue with balking, reneging, and vacation interruption under -policy. In the working vacation, a customer is served at a lower rate and at the instants of a service completion; if there are at least customers in the queue, the vacation is interrupted and the server switches to regular busy period otherwise continues the vacation. Using Markov process and recursive technique, we derive the stationary system length distributions at arbitrary epoch. Various performance measures and some special models of the system are presented. Cost analysis is carried out using particle swarm optimization and quadratic fit search method. Finally, some numerical results showing the effect of model parameters on key performance measures of the system are presented. P. Vijaya Laxmi, V. Goswami, and K. Jyothsna Copyright © 2013 P. Vijaya Laxmi et al. All rights reserved. Optimization of Integer Order Integrators for Deriving Improved Models of Their Fractional Counterparts Sat, 22 Jun 2013 14:54:01 +0000 Second and third order digital integrators (DIs) have been optimized first using Particle Swarm Optimization (PSO) with minimized error fitness function obtained by registering mean, median, and standard deviation values in different random iterations. Later indirect discretization using Continued Fraction Expansion (CFE) has been used to ascertain a better fitting of proposed integer order optimized DIs into their corresponding fractional counterparts by utilizing their refined properties, now restored in them due to PSO algorithm. Simulation results for the comparisons of the frequency responses of proposed 2nd and 3rd order optimized DIs and proposed discretized mathematical models of half integrators based on them, with their respective existing operators, have been presented. Proposed integer order PSO optimized integrators as well as fractional order integrators (FOIs) have been observed to outperform the existing recently published operators in their respective domains reasonably well in complete range of Nyquist frequency. Maneesha Gupta and Richa Yadav Copyright © 2013 Maneesha Gupta and Richa Yadav. All rights reserved. Designing a Fuzzy Strategic Integrated Multiechelon Agile Supply Chain Network Wed, 19 Jun 2013 09:16:23 +0000 This paper integrates production, distribution and logistics activities at the strategic decision making level, where the objective is to design a multiechelon supply chain network considering agility as a key design criterion. A network with five echelons of supply chains including suppliers, plants, distribution centers, cross-docks, and customer zones is addressed in this paper. The problem has been mathematically formulated as a biobjective optimization model that aims to minimize the cost (fixed and variable) and maximize the plant flexibility and volume flexibility. A novel multiobjective parallel simulating annealing algorithm (MOPSA) is proposed to obtain the Pareto-optimal solutions of the problem. The performance of the proposed solution algorithm is compared with two well-known metaheuristics, namely, nondominated sorting genetic algorithm (NSGA-II) and Pareto archive evolution strategy (PAES). Computational results show that MOPSA outperforms the other metaheuristics. Morteza Abbasi, Reza Hosnavi, and Mehrdad Mohammadi Copyright © 2013 Morteza Abbasi et al. All rights reserved. A Hybrid PSO-Fuzzy Model for Determining the Category of 85th Speed Thu, 13 Jun 2013 14:33:21 +0000 The 85th speed of vehicles is one of the traffic engineering parameters used by road safety equipment designers. It is usually used for maintenance activities and designing of warning signs and road equipments. High measuring costs of speed data collection lead decision makers to define a methodology for determining the category of 85th speed using indirect parameters. In this research work, focusing on undivided intercity roads, a hybrid particle-swarm-optimization- (PSO-) fuzzy model has been developed to determine the category of 85th speed. In this model, geometric design parameters including roads' width and length characteristics and roadside land use are considered as input variables whereas the category of the 85th speed is output variable. A set of experimental data is used for evaluating the performance of the proposed model comparing to a well-known model of exponential regression. It is shown that the developed PSO-fuzzy model is capable of determining the category of 85th speed with an accuracy of 96%, while exponential regression can estimate that with up to 84% accuracy. Variable effectiveness procedure shows that the lane width has more direct effect on 85th speed than shoulder width and the number of access points. The percentage of forbidden overtaking is also found to have indirect effect on 85th speed. Abbas Mahmoudabadi and Ali Ghazizadeh Copyright © 2013 Abbas Mahmoudabadi and Ali Ghazizadeh. All rights reserved. Physics-Inspired Optimization Algorithms: A Survey Wed, 12 Jun 2013 10:51:39 +0000 Natural phenomenon can be used to solve complex optimization problems with its excellent facts, functions, and phenomenon. In this paper, a survey on physics-based algorithm is done to show how these inspirations led to the solution of well-known optimization problem. The survey is focused on inspirations that are originated from physics, their formulation into solutions, and their evolution with time. Comparative studies of these noble algorithms along with their variety of applications have been done throughout this paper. Anupam Biswas, K. K. Mishra, Shailesh Tiwari, and A. K. Misra Copyright © 2013 Anupam Biswas et al. All rights reserved. Image Watermarking Algorithm Based on Multiobjective Ant Colony Optimization and Singular Value Decomposition in Wavelet Domain Thu, 06 Jun 2013 09:39:21 +0000 We present a new optimal watermarking scheme based on discrete wavelet transform (DWT) and singular value decomposition (SVD) using multiobjective ant colony optimization (MOACO). A binary watermark is decomposed using a singular value decomposition. Then, the singular values are embedded in a detailed subband of host image. The trade-off between watermark transparency and robustness is controlled by multiple scaling factors (MSFs) instead of a single scaling factor (SSF). Determining the optimal values of the multiple scaling factors (MSFs) is a difficult problem. However, a multiobjective ant colony optimization is used to determine these values. Experimental results show much improved performances of the proposed scheme in terms of transparency and robustness compared to other watermarking schemes. Furthermore, it does not suffer from the problem of high probability of false positive detection of the watermarks. Khaled Loukhaoukha Copyright © 2013 Khaled Loukhaoukha. All rights reserved. Power Optimization of Tilted Tomlinson-Harashima Precoder in MIMO Channels with Imperfect Channel State Information Wed, 22 May 2013 15:52:40 +0000 This paper concentrates on the designing of a robust Tomlinson-Harashima Precoder (THP) over multiple-input multiple-output (MIMO) channels in wireless communication systems with assumption of imperfect channel state information (CSI) at the transmitter side. With the assumption that the covariance matrix of channel estimation error is available at the transmitter side, we design a THP that presents robustness against channel uncertainties. In the proposed robust THP, the transmit power is further minimized by using the Tilted constellation concept. This power minimization reduces the interchannel Interference (ICI) between subchannels and, furthermore, recovers some part of the THP's power loss. The bit error rate (BER) of the proposed system is further improved by using a power loading technique. Finally, the simulation results compare the performance of our proposed robust THP with a conventional MIMO-THP. Hossein Khaleghi Bizaki, Morteza Khaleghi Hojaghan, and Seyyed Mohammad Razavizadeh Copyright © 2013 Hossein Khaleghi Bizaki et al. All rights reserved. Optimizing the Two-Stage Supply Chain Inventory Model with Full Information Sharing and Two Backorders Costs Using Hybrid Geometric-Algebraic Method Mon, 13 May 2013 15:02:51 +0000 We consider the case of a two-stage serial supply chain system. This supply chain system involves a single vendor who supplies a single buyer with a single product. The vendor’s production rate is assumed finite. In addition, the demand at the buyer is assumed deterministic. In order to coordinate their replenishment policies and jointly optimize their operational costs, the two supply chain partners fully share their relevant information. For this purpose, we develop an integrated inventory replenishment model assuming linear and fixed backorders costs. Then, we use a hybrid geometric-algebraic method to drive the optimal replenishment policy and the minimum supply chain total cost in a closed form. Mohamed E. Seliaman Copyright © 2013 Mohamed E. Seliaman. All rights reserved. Particle Swarm Optimization for Multiband Metamaterial Fractal Antenna Tue, 23 Apr 2013 15:47:28 +0000 The property of self-similarity, recursive irregularity, and space filling capability of fractal antennas makes it useful for various applications in wireless communication, including multiband miniaturized antenna designs. In this paper, an effort has been made to use the metamaterial structures in conjunction with the fractal patch antenna, which resonates at six different frequencies covering both C and X band. Two different types of square SRR are loaded on the fractal antenna for this purpose. Particle swarm optimization (PSO) is used for optimization of these metamaterial structures. The optimized metamaterial structures, after loading upon, show significant increase in performance parameters such as bandwidth, gain, and directivity. Balamati Choudhury, Sangeetha Manickam, and R. M. Jha Copyright © 2013 Balamati Choudhury et al. All rights reserved.