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The article discusses the result of an experimental study which shows that people do not follow the optimal strategy in practice and suggests two strategies for defeating human opponents in rock-paper-scissors (RPS). The study found that the probability of repeating a game on the next trial is well above one-third, while the strategy of always playing the symbol is assessed to be an effective strategy in defeating the symbol that the other player has previously played. The study also observed that the wins of each competition have increased by 26.4%, while the losses are decreased by 9.51%.

With this note, we want to open a discussion on the duality theory for Interval Optimization. We begin by showing that some duality results Wu ( J Optim Theory Appl 144:615-628, ) are useless. [ABSTRACT FROM AUTHOR]

The optimization of functions to find the best solution according to one or several objectives has a central role in many engineering and research fields. Recently, a new family of optimization algorithms, named quality-diversity (QD) optimization, has been introduced, and contrasts with classic algorithms. Instead of searching for a single solution, QD algorithms are searching for a large collection of both diverse and high-performing solutions. The role of this collection is to cover the range of possible solution types as much as possible, and to contain the best solution for each type. The contribution of this paper is threefold. First, we present a unifying framework of QD optimization algorithms that covers the two main algorithms of this family (multidimensional archive of phenotypic elites and the novelty search with local competition), and that highlights the large variety of variants that can be investigated within this family. Second, we propose algorithms with a new selection mechanism for QD algorithms that outperforms all the algorithms tested in this paper. Lastly, we present a new collection management that overcomes the erosion issues observed when using unstructured collections. These three contributions are supported by extensive experimental comparisons of QD algorithms on three different experimental scenarios. [ABSTRACT FROM PUBLISHER]

Rufus P. Isaacs joined the RAND Corporation4. Santa Monica, California in 1948 and started to develop the theory of dynamic games in the early 1950s. Until winter 1954/55, when Isaacs left the RAND Corporation, he investigated two player. zero-sum dynamic games of the classic pursuit-evasion type. Prior to 1965, Isaacs published his theory only in internal RAND papers and research memoranda. In his first RAND paper (Ref. 1), Isaacs sketched the basic ideas of zero-sum dynamic game theory The ideas already included rudimentary precursors of the maximum principle, dynamic programming, and backward analysis. At the end of 1954 and the beginning of 1955. Isaacs summarized his research in four research memoranda (Refs. 3–6), which ten years later formed the basis of his famous book on Differential Games (Ref. 7). This paper survey's Isaacs' research with an emphasis on the early years of dynamic games. The readers are kindly invited to discuss the author's point of view. Comments and statements sent to the author will be summarized and published later. [ABSTRACT FROM AUTHOR]

In this paper, we are trying to find the optimum solution of a transportation problem and is to minimize the cost. The most attractive feature of this method is that it requires very simple arithmetical and logical calculation, which compared to the existing method an optimal solution and illustrated with numerical example. [ABSTRACT FROM AUTHOR]

Generally speaking, spoken term detection system will degrade significantly because of mismatch between acoustic model and spontaneous speech. This paper presents an improved spoken term detection strategy, which integrated with a novel phoneme confusion matrix and an improved word-level minimum classification error (MCE) training method. The first technique is presented to improve spoken term detection rate while the second one is adopted to reject false accepts. On mandarin conversational telephone speech (CTS), the proposed methods reduce the equal error rate (EER) by 8.4% in relative. [ABSTRACT FROM AUTHOR]

In this paper we have proposed a nonlinear mathematical model for a wind turbine. The objective function maximizes the power of the wind turbine and the constraints are related to the rotor and tower costs. Rotor diameter and hub height are the variables which affect on power of the wind turbine, so we have considered them as decision variable in our mathematical model. By increasing rotor diameter and hub height the power of the turbine will increase but the costs don't let the infinitive increase in rotor diameter and height. The model applied for a typical case study and the results of solving the model for it have shown in the paper. [ABSTRACT FROM AUTHOR]

Due to outstanding light shaping potential, freeform optical surfaces have been considered theoretically from centuries. Recently, they gained increased interest due to the availability of manufacturing technologies. Nevertheless, the design of freeform surfaces still becomes a challenge, associated with advanced mathematical concepts and significant computing power. In this work, a very interesting unification of theories is mentioned. It is shown how the problem of optimal redistribution of mass, analyzed in the 18th century, corresponds to the problem of optical beam shaping realized by freeform surface. Both issues are governed by the same partial differential equation. In the paper, a novel numerical algorithm for solving this partial differential equation is discussed. As an example, a design of freeform lens, capable of casting completely arbitrary shapes, is presented. [ABSTRACT FROM AUTHOR]

Optimization of any aerospace product results in increasing payload capacity of space vehicles. Essentially weight, volume and cost are the main constraints. Design optimization studies for aerospace system are increasingly gaining importance. The problem of optimum design under uncertainty has been formulated as reliability-based design optimization. The reliability based optimization, which includes robustness requirements leads to multi-objective optimization under uncertainty. In this paper Reliability, based design optimization study is carried out under linear constraint optimization to minimize the weight of a nitrogen gas bottle with specified target reliability. Response surface method considering full factorial experiment is used to establish multiple regression equation for induced hoop stress and maximum strain. Necessary data pertaining to design, manufacturing and operating conditions are collected systematically for variability study. Structural reliability is evaluated using Advanced First-Order Second-Moment Method (AFOSM). Finally, optimization formulation established and it has been discussed in this paper. [ABSTRACT FROM AUTHOR]

We study the uniqueness and explicit derivation of the relaxed optimal solutions, corresponding to the minimization of weighted sum of potential energies for a mixture of two isotropic conductive materials on an annulus. Recently, it has been shown by Burazin and Vrdoljak that even for multiple-state problems, if the domain is spherically symmetric, then the proper relaxation of the problem by the homogenization method is equivalent to a simpler relaxed problem, stated only in terms of local proportions of given materials. This enabled explicit calculation of a solution on a ball, while problems on an annulus appeared to be more tedious. In this paper, we discuss the uniqueness of a solution of this simpler relaxed problem, when the domain is an annulus and we use the necessary and sufficient conditions of optimality to present a method for explicit calculation of the unique solution of this simpler proper relaxation, which is demonstrated on an example. [ABSTRACT FROM AUTHOR]

Time consistency is one of desirable properties for any solution of a cooperative dynamic game. If a solution is time-consistent, the players do not need to break a cooperative agreement. In this paper, we consider the core as the solution and establish conditions for its strong time consistency. When the core is not strongly time-consistent, we show that in some cases its elements can be yielded using a strongly time-consistent imputation distribution procedure. An explicit form of the procedure is given. [ABSTRACT FROM AUTHOR]

In this paper, a new group of optimization algorithms named Human Strategy Algorithm (HS) is proposed which is inspired by human strategies to problem solving. The main idea of HS is based on human actions to find the problem’s optima by means of accessible instruments. As the environment of an unknown problem assumed to be a black box, it is supposed that the environment of our problem is a dark room occupied by several men named blind men. The main mission of these men is to look for the optimum solution. Each man has at least one instrument as his assistance. Like real life, the instrument might be any tool such as stick, billy, rope, stone, yoyo, sweep. Any instrument by its unique features is suitable in some situations. In fact, this algorithm maps problem space and searches agents to dark room and people, respectively. In this paper, one sample algorithm of the group of human strategy, YOYO Blind Man Algorithm (YOYO-BMA), is introduced which uses yoyos as men’s accessible instruments. The performance of the YOYO-BMA is evaluated on a set of benchmark problems provided for CEC’2010 Special Session and Competition on Large-Scale Global Optimization (Tang et al. 2010). The results show superior performance of proposed algorithm in comparison with others. Moreover, the problem of designing urban traffic network is solve to evaluate the algorithm using a real complex problem. [ABSTRACT FROM AUTHOR]

Hub locations are NP-hard problems used in transportation systems. In this paper, we focus on a single-allocation hub covering location problem considering a queue model in which the number of servers is a decision variable. We propose a model enhanced with a queue estimation component to determine the number and location of hubs and the number of servers in each hub, and to allocate non-hub to hub nodes according to network costs, including fixed costs for establishing each hub and server, transportation costs, and waiting costs. Moreover, we consider the capacity for a queuing system in any hub node. In addition, we present a metaheuristic algorithm based on particle swarm optimization as a solution method. To evaluate the quality of the results obtained by the proposed algorithm, we establish a tight lower bound for the proposed model. Genetic programming is used for lower bound calculation in the proposed method. The results showed better performance of the proposed lower bound compared to a lower bound obtained by a relaxed model. Finally, the computational results confirm that the proposed solution algorithm performs well in optimizing the model with a minimum gap from the calculated lower bound. [ABSTRACT FROM AUTHOR]

This paper is concerned with the lag quasi-synchronization for memristive neural networks (MNNs) with switching jumps mismatch. The inherent characteristic of MNNs is fully taken into account. Based on Lyapunov-Krasovskii functional and differential inclusions theory, intermittent control approach is utilized to realize the exponential lag quasi-synchronization of the considered model. The error level is closely related to the switching jumps. In addition, a simple design procedure of controller is presented to ensure that the synchronization error between the master system and the slave system converges to a predetermined level. Two numerical examples are offered to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of query optimization in relational distributed database systems. It concentrates on the development of heuristic procedures that attempt to minimize the communication costs incurred by the distributed processing of queries. In particular, the paper deals with a class of heuristics that use a semi-join strategy as the mechanism for communication cost reduction. These heuristics are classified into two types — local and global heuristics. The global heuristic proposed in this paper is based on an optimal solution to a mathematical model of a simplified version of the problem. It is shown that the global heuristic can generate beneficial semi-join operations not included in local heuristic solutions. [ABSTRACT FROM AUTHOR]

Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This paper considers the design of hierarchical (communication) networks. We consider the survivability of asymmetrical hierarchical network flows (AHNF), when arcs failure and, hence, flow destruction is probable. In such networks, it is supposed that the remaining arc capacities are known and the guaranteed evaluation of the functional capability assumes finding the worst distribution of flow in the destructed network. Since, in the network flows, a unique efficiency criterion is not generally known or defined, we assess the quality of the network functioning by a measure of demands satisfaction, i.e. the fraction of satisfied demands at the sink nodes. With regard to this criterion, we construct the mathematical model of the network regardless of the design structure. Then, by defining a measure of satisfying the demands, we compute and compare the survivability of two well-known reserve designs, namely radial and circular reserves. [ABSTRACT FROM AUTHOR]

In this paper, the impulsive Cohen-Grossberg neural network with unbounded discrete time-varying delays is considered. By using the analysis method and inequality technique, several sufficient conditions are obtained to ensure the global exponential stability of the addressed neural network. These results generalize the existing relevant stability results. Two examples with simulations are given to show the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

This short correspondence is a reply to a recently published paper by Verlinde et al. in which the authors empirically compared fuzzy and nonfuzzy association analysis and, on the basis of their results, questioned the usefulness of a fuzzy approach. Although we highly welcome the critical examination of the topic and definitely agree that fuzzy extensions of existing methods call for a thorough justification, the empirical comparison presented in the aforementioned paper is in our opinion not objective and extensive enough to fully warrant the conclusions drawn from the results. Apart from some general comments on the claims raised in their paper, we present empirical results based on an alternative experimental setup that lead to different conclusions. [ABSTRACT FROM AUTHOR]

It is well known that all betting systems applied to independent, repeated, and identically distributed trials will result in the same expected gain per average unit wagered as that which applies to a single trial. This paper develops the asymptotic and paradoxical manner in which that constant win rate is maintained for optimal proportional betting according to the Kelly criterion. The appropriateness of using this traditional measure of win rate for proportional betting is contrasted with that of various alternatives. [ABSTRACT FROM AUTHOR]

A model for estimating the transient performance of assembly networks is presented in this paper. Based on the fundamental assumption that operation start and finish times are related by the multivariate normal distribution, the approach relies upon computational procedures for estimating the correlations between certain operation finishing times. Fundamental properties of these correlations are identified and used to develop a procedure for estimating transient performance. Evaluated in a set of hypothetical test cases, the approach gave estimates which compare favorably with those derived from a simulation model both in accuracy and runtime. The approach is demonstrated as a decision aid in a case study involving material flow planning. Test results indicate that the approach offers unique capability to model transient operations in assembly networks. [ABSTRACT FROM AUTHOR]

Ordered weighted average (OWA) operator provides a parameterized class of mean type operators between the minimum and the maximum. It is an important tool that can reflect the strategy of a decision maker for decision‐making problems. In this study, the idea of obtaining the stress function from OWA weights has been put forward to generalize and characterize OWA weights. The main idea in this paper is mainly constructed on the basis that, generally, stress functions can be constructed using a mixture of constant and linear components. So, we can consider the stress function as a piecewise linear function. For obtaining stress functions as piecewise linear functions, we present a clustering‐based approach for OWA weight generalization. This generalization is made using the DBSCAN algorithm as the learning method of a stress function associated with known OWA weights. In the learning process, the whole data set is divided into clusters, and then linear functions are obtained via a least squares estimator. [ABSTRACT FROM AUTHOR]

This paper presents a shape sensitivity analysis and what-if study for two-dimensional multi-scale crack propagation problems using bridging scale decomposition. The sensitivity equations are derived in a continuum setting using direct differentiation method based on a continuum variational formulation of the bridging scale. Due to the fact that the crack propagation speed in an atomistic simulation is discrete in design, and cannot be formulated as a continuous function of shape design variables, we propose a hybrid method that combines analytical sensitivity analysis with finite difference approach. The finite difference part of the sensitivity analysis is only intended for calculating the sensitivity of crack growth speed based on the analytically obtained sensitivity coefficients of structural responses. The theoretical development on sensitivity formulation in this paper extends the application of the method to irregular-shaped finite elements and general design velocity fields. Furthermore, we evaluate and compare several performance measures that quantify crack propagation speed based on crack tip locations for sensitivity analysis and ultimately for structural optimization. A two-dimensional beam example is used to verify the accuracy of the proposed sensitivity approach. It is also demonstrated through a what-if study that with an adequate performance measure, the impact of macroscopic shape changes on microscopic crack propagation speed can be accurately predicted. [ABSTRACT FROM AUTHOR]

An accurate mathematical model has a vital role in controlling and synchronization of chaotic systems. But generally in real-world problems, parameters are mixed with mismatches and distortions. This paper proposes two simple but effective estimation methods to detect the unknown parameters of chaotic models. These methods focus on improving the performance of a recently proposed evolutionary algorithm called backtracking search optimization algorithm (BSA). In this research firstly, a new operator to generate initial trial population is proposed. Then a group search ability is provided for the BSA by proposing a shuffled BSA (SBSA). Grouping population into several sets can provide a better exploration of search space, and an independent local search of each group increases exploitation ability of the BSA. Also new proposed operator to generate initial trial population, by providing a deep search, increases considerably the quality of solutions. The superiority of the proposed algorithms is investigated on parameter identification of 10 typical chaotic systems. Practical experiences and nonparametric analysis of obtained results show that both of the proposed ideas to improve performance of original BSA are very effective and robust so that the BSA by aforementioned ideas produces similar and promising results over repeated runs. A considerably better performance of proposed algorithms based on average of objective functions demonstrates that the proposed ideas can evolve robustness and consistence of BSA. A comparison of the proposed algorithms in this study with respect to other algorithms reported in the literature confirms a considerably better performance of proposed algorithms. [ABSTRACT FROM AUTHOR]

The inverse radiative transfer problem finds broad applications in medical imaging, atmospheric science, astronomy, and many other areas. This problem intends to recover optical properties, denoted as absorption and the scattering coefficient of the media, through source-measurement pairs. A typical computational approach is to form the inverse problem as a PDE-constraint optimization, with the minimizer being the to-be-recovered coefficients. The method is tested to be efficient in practice, but it lacks analytical justification: there is no guarantee of the existence or uniqueness of the minimizer, and the error is hard to quantify. In this paper, we provide a different algorithm by levering the ideas from singular decomposition analysis. Our approach is to decompose the measurements into three components, two of which encode the information of the two coefficients, respectively. We then split the optimization problem into two subproblems and use those two components to recover the absorption and scattering coefficients separately. In this regard, we prove the well-posedness of the new optimization, and the error could be quantified with better precision. In the end, we incorporate the diffusive scaling and show that the error is harder to control in the diffusive limit. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method to estimate the probability distribution of the time interval which ellapses between the modifications of the cardinality in a random database query's result set. This type of database is important either in modeling uncertainty or storing data whose values follow a probability distribution. The result that we introduce is important from the point of view of the database optimization, providing a useful method for an integrated module. In previous research on random databases the sizes of some relational operations results were investigated. This kind of information is rather useful in an analytical database which provides decision-making support. The result we particularly aim to present in this paper concerns the transactional random databases, addressing its specific functionality. It will be proven that the interval of time between the cardinalities changes is exponentially distributed. The proof is based on the technique of the Markovian Jelinski-Moranda model, which is used in the reliability of software programs. [ABSTRACT FROM AUTHOR]

Rough sets, developed by Pawlak [15], are important tool to describe situation of incomplete or partially unknown information. In this article we give the formal characterization of two closely related rough approximations, along the lines proposed in a paper by Gomolinska [2]. We continue the formalization of rough sets in Mizar [1] started in [6]. [ABSTRACT FROM AUTHOR]

State/event linear temporal logic (SE-LTL) provides a concise and intuitive way to express properties incorporating both states and events. Automata-theoretic LTL model checking can be applied to verify SE-LTL properties. However, as SE-LTL is not preserved under classical stutterequivalence, conventional partial order reduction (POR) cannot be directly used to check them. In this paper, we propose a novel approach to exploit POR for reducing the state space with respect to SE-LTL formulas. This approach detects a 'state part' of a Büchi automaton (BA) translated from an SE-LTL formula. Based on 'state part', we introduce a definition of SPs of BAs and labeled Kripke structures (LKS) with the integration of POR for reducing the state spaces of the products. The integrated POR modifies conventional POR by introducing an identification of visible actions with respect to events. Moreover, in order to apply POR to the full class of SE-LTL, we provide techniques to exploit POR for checking SE-LTL with the nexttime operator. We have implemented our techniques in SPIN model checker. The experimental results illustrate the potential of the techniques for reduction compared with pure state-based model checking and SE-LTL model checking without POR. [ABSTRACT FROM AUTHOR]

In this paper, we propose a decentralized parallel computation model for global optimization using interval analysis. The model is adaptive to any number of processors and the workload is automatically and evenly distributed among all processors by alternative message passing. The problems received by each processor are processed based on their local dominance properties, which avoids unnecessary interval evaluations. Further, the problem is treated as a whole at the beginning of computation so that no initial decomposition scheme is required. Numerical experiments indicate that the model works well and is stable with different number of parallel processors, distributes the load evenly among the processors, and provides an impressive speedup, especially when the problem is time-consuming to solve. [ABSTRACT FROM AUTHOR]

It is with a great significance to discuss the selection model of regional strategic emerging industry. First, the paper uses the fuzzy optimization theory to select the central industry of area as the regional strategic emerging industry and try to optimize the weight's calculation in the multistage fuzzy comprehensive evaluation to get more accurate results. Then it will do a strategic emerging industrial inspection about the advantage and ecological related index based on a multiobjective programming model and the maximum entropy. [ABSTRACT FROM AUTHOR]

The disassembly line is the best choice for automated disassembly of disposal products. Therefore, disassembly line should be designed and balanced so that it can work as efficiently as possible. In this paper, a mathematical model for the multi-objective disassembly line balancing problem is formalized firstly. Then, a novel multi-objective ant colony optimization (MOACO) algorithm is proposed for solving this multi-objective optimization problem. Taking into account the problem constraints, a solution construction mechanism based on the method of tasks assignment is utilized in the algorithm. Additionally, niche technology is used to embed in the updating operation to search the Pareto optimal solutions. Moreover, in order to find the Pareto optimal set, the MOACO algorithm uses the concept of Pareto dominance to dynamically filter the obtained non-dominated solution set. To validate the performance of algorithm, the proposed algorithm is measured over published results obtained from single-objective optimization approaches and compared with multi-objective ACO algorithm based on uniform design. The experimental results show that the proposed MOACO is well suited to multi-objective optimization in disassembly line balancing. [ABSTRACT FROM AUTHOR]

Both response time and processing time become recently big problems in the processing time of various online and batch systems. Especially, the access efficiency of the database should be greatly controlled as for the speed of the processing time of accesses to the database. Because records are inserted far from their logical position, the storages of deleted records occupy some diverse spaces in the database. Then, to cover the weak point of the database, we execute the database reorganization at suitable times to achieve a good performance requirement for the application. There are two types purposes of the database reorganization: The purpose of physical reorganization is to optimize the database storage and to improve the database structure. However, as the database has usually access locality, its data structure may deterirate in limited parts of the storage space. Thus, we adop the partial reorganization. This reorganizes only locally structurally deteriorated space in the database, while the structural efficiency can be recovered similarly to the full reorganization. This paper considers two structural deteriorations which increase with time and occur independently in time. When the amount of deterioration is estimated at periodic time and at a specified time, the expected cost rates are obtained, using the cumulative damage model, and optimal policies which minimize them are discussed and analytically. We compute optimal policies for two models and compare them numeically. [ABSTRACT FROM AUTHOR]

This paper considers the problem of searching for the actual time of failure for a system when the only information that is available is that it is has failed by a time t. This situation can be analyzed by using the concept of the reversed failure rate. This paper considers optimization problems that can be solved by using the reversed failure rate. When a unit is detected to have failed at time t, we discuss an optimum backward time from time t to search for its failure time which minimizes the expected cost. The recovery of a database system and of reweighing products using a scale are taken to be two typical applications of the backward time concept. Two models are proposed for appropriate maintenance actions for these situations when a unit is detected to have failed at time t. [ABSTRACT FROM AUTHOR]

This paper considers a stochastic variational inequality problem (SVIP). We first formulate SVIP as an optimization problem (ERM problem) that minimizes the expected residual of the so-called regularized gap function. Then, we focus on a SVIP subclass in which the function involved is assumed to be affine. We study the properties of the ERM problem and propose a quasi-Monte Carlo method for solving the problem. Comprehensive convergence analysis is included as well. [ABSTRACT FROM AUTHOR]

We present a new computational approach to the problem of placing n identical nonoverlapping disks in the unit square in such a way that their radii are maximized. The problem has been studied in a large number of papers, from both a theoretical and a computational point of view. In this paper, we conjecture that the problem possesses a so-called funneling landscape, a feature that is commonly found in molecular conformation problems. Based on this conjecture, we develop a stochastic search algorithm that displays excellent numerical performance. Thanks to this algorithm, we could improve over previously known putative optima in the range n ≤ 130 in as many as 32 instances, the smallest of which is n=53. [ABSTRACT FROM AUTHOR]

Abstract  Based on the concept of general domination structures, this paper presents an approach to model variable preferences for multicriteria optimization and decision making problems. The preference assumptions for using a constant convex cone are given, and, in remedy of some immanent model limitations, a new set of assumptions is presented. The underlying preference model is derived as a variable domination structure that is defined by a collection of ideal-symmetric convex cones. Necessary and sufficient conditions for nondominance are established, and the problem of finding corresponding nondominated solutions is addressed and solved on examples. [ABSTRACT FROM AUTHOR]

In this paper, we describe the H-differentials of some well known NCP functions and their merit functions. We show how, under appropriate conditions on an H-differential of f, minimizing a merit function corresponding to f leads to a solution of the nonlinear complementarity problem. Our results give a unified treatment of such results for C 1-functions, semismooth-functions, and locally Lipschitzian functions. Illustrations are given to show the usefulness of our results. We present also a result on the global convergence of a derivative-free descent algorithm for solving the nonlinear complementarity problem. [ABSTRACT FROM AUTHOR]

Abstract  This paper presents a general approach toward the optimal selection and ensemble (weighted average) of kernel-based approximations to address the issue of model selection. That is, depending on the problem under consideration and loss function, a particular modeling scheme may outperform the others, and, in general, it is not known a priori which one should be selected. The surrogates for the ensemble are chosen based on their performance, favoring non-dominated models, while the weights are adaptive and inversely proportional to estimates of the local prediction variance of the individual surrogates. Using both well-known analytical test functions and, in the surrogate-based modeling of a field scale alkali-surfactant-polymer enhanced oil recovery process, the ensemble of surrogates, in general, outperformed the best individual surrogate and provided among the best predictions throughout the domains of interest. [ABSTRACT FROM AUTHOR]

AbstractThe main objective of this paper was to develop a mathematical model to predict the surface roughness and to determine the optimal cutting conditions during milling of medium density fiberboard. The milling experiments were carried out as per Taguchi orthogonal array with feed rate and cutting speed as the controlling parameters. A second-order surface roughness model has been developed using the methodology of response surface analysis. The paper presents the details of analysis of variance to validate the developed model. The Taguchi optimization results show that the surface roughness can be optimized with lower feed rate and higher cutting speed values. [ABSTRACT FROM AUTHOR]

Relaxed controls have proved to be very useful in studying the existence of optimal controls in optimal control theory. Many positive results have been obtained in the literature. However, negative results have also made their rare appearances. The optimal control problem considered in this paper looks quite simple. Yet, by treating such a problem, we can get interesting results, substantiating our idea as to whether an optimal control exists or not. In our opinion, the method used in the paper can be applied to more generalized cases. [ABSTRACT FROM AUTHOR]

In this paper the authors study a model for the optimal operation of a bank or insurance company which was recently introduced by Peura and Keppo. The model generalizes a previous one of Milne and Robertson by allowing the bank to raise capital as well as to pay out dividends. Optimal operation of the bank is determined by solving an optimal control problem. In this paper it is shown that the solution of the optimal control problem proposed by Peura and Keppo exists for all values of the parameters and is unique. [ABSTRACT FROM AUTHOR]

This paper presents a novel evolutionary algorithm (EA) for constrained optimization problems, i.e., the hybrid constrained optimization EA (HCOEA). This algorithm effectively combines multiobjective optimization with global and local search models. In performing the global search, a niching genetic algorithm based on tournament selection is proposed. Also, HCOEA has adopted a parallel local search operator that implements a clustering partition of the population and multiparent crossover to generate the offspring population. Then, nondominated individuals in the offspring population are used to replace the dominated individuals in the parent population. Meanwhile, the best infeasible individual replacement scheme is devised for the purpose of rapidly guiding the population toward the feasible region of the search space. During the evolutionary process, the global search model effectively promotes high population diversity, and the local search model remarkably accelerates the convergence speed. HCOEA is tested on 13 well-known benchmark functions, and the experimental results suggest that it is more robust and efficient than other state-of-the-art algorithms from the literature in terms of the selected performance metrics, such as the best, median, mean, and worst objective function values and the standard deviations. [ABSTRACT FROM AUTHOR]

In this paper we develop an optimization approach for the study of adverse drug reaction (ADR) problems. This approach is based on drug–reaction relationships represented in the form of a vector of weights, which can be defined as a solution to some global optimization problem. Although it can be used for solving many ADR problems, we concentrate on two of them here: the accurate identification of drugs that are responsible for reactions that have occurred, and drug–drug interactions. Based on drug–reaction relationships, we formulate these problems as an optimization problem. The approach is applied to cardiovascularn-type reactions from the Australian Adverse Drug Reaction Advisory Committee (ADRAC) database. Software based on this approach has been developed and could have beneficial use in prescribing. [ABSTRACT FROM AUTHOR]

Abstract??Experiments in real life often involve comparisons of test treatments to more than one control. However, the controls may not always be of equal importance. In this paper we introduce weighted MV optimality criterion and present a detailed study using both weighted A and MV optimality criteria, of the problem of optimally comparing a set of test treatments to two controls (positive and a negative) that are of unequal importance to the experimenter. [ABSTRACT FROM AUTHOR]

OBEX (Object Exchange Protocol) is a session protocol designed to exchange all kind of objects between portable devices using different ad hoc wireless links including IrDA and Bluetooth. This paper develops a mathematical model for OBEX over the IrDA protocol stack by considering multiple applications and presence of bit errors. The model is also verified by simulation results. We derive throughput equations and carry out an optimization study focusing on four major parameters: OBEX packet size, TinyTP (IrDA transport layer) buffer size, IrLAP (IrDA link layer) frame and window size. Equations are derived for the optimum IrLAP window and frame sizes. Numerical results show significant improvement on OBEX performance using the optimized parameters. The major contribution of this work is the modelling of OBEX including the low layer protocols and optimization of the overall throughput by appropriate parameter selection. [ABSTRACT FROM AUTHOR]

In this paper, the property of a necessary second-order optimality condition to hold with the same Lagrange multiplier for all critical vectors is investigated. It is limited to nonconvex optimization problems in &IRlig;n with equality and inequality constraints; the Mangasarian-Fromovitz constraint qualification is assumed to hold. A counterexample was given recently by Anitescu. We give some sufficient conditions and we prove that this property holds if n ≤ 2 or if the number of active inequality constraints is at most two. For three active inequality constraints and n = 3, a counterexample is given. [ABSTRACT FROM AUTHOR]