A structured approach to program optimization

Software engineering should provide software engineers with methodologies and tools suitable for use in that small number of applications where efficiency is really important. In order to do that, the optimization process should be a clearly visible phase of the software lifecycle (regardless of the particular software development paradigm adopted), so that it can be regulated, securing the production of good quality and efficient software. With this in mind, the author suggests an approach to program optimization based on a paradigm, a method, some principles and guidelines, and some well-known techniques     

A generalized approach to fuzzy optimization

A new approach to fuzzy optimization based on the generalization of Bellman-Zadeh's (BZ) concept is proposed in this article. It consists of a parametric generalization of intersection of fuzzy sets and a generalized defuzzification method. This approach allows the solving of a fuzzy mathematical programming (FMP) problem without transformation to a crisp one. It takes into account all possible fuzzy decisions and allows the degree of conjunction of criteria and constraints to vary. BZ method can be considered a special case of the approach proposed here. A simple algorithm for noniterative solving FMP problem is proposed whereas well-known Zimmermann's approach uses numerical methods. an illustrative example is presented. © 1994 John Wiley & Sons, Inc.     

A novel approach to LCD optimization

Abstract— A novel approach to optimization liquid‐crystal displays (LCDs) is presented. The optimization module allows for a prediction with a high accuracy for the best results, which can be obtained for one or the other configuration of the polarizers and phase retarders in various electro‐optical modes, if the LC parameters and the operating voltages are fixed. The module is a part of our program, MOUSE‐LCD, which is efficient software for LCD optimization and modeling.     

A systems theoretical approach to online knowledge building

This article describes the phenomenon of knowledge building in online environments. Knowledge building is a process within a community, which leads to the development of knowledge. In order to analyze this process, we will look into the ways in which individuals interact with the collective as a whole. For this purpose, the psychic and social systems, which are involved here are regarded as meaning-based systems in the sense of Luhmann’s systems theory—open to the environment, but operatively closed. The respective modes of operation of psychic and social systems will be examined, and “structural coupling” between these systems described. Another characteristic of knowledge-building communities is self-organization, which is described here in the sense of autopoiesis. A pivotal task, which knowledge-building communities have to tackle, is to handle complexity and reach common understanding. These aspects will also be described using conceptualizations of Luhmann’s systems theory, illustrated by many examples.     

A method for system identification using the optimality criteria optimization approach

An algorithm similar to the optimality criteria approach used in structural optimization is presented for identifying stiffnesses of structural members by using vibration test data. A set of equivalent static inertia forces are obtained from the vibration analysis using d'Alembert's principle and are used to solve the multiple displacement constraint problem. The displacement constraint values are specified based on the measured experimental modal displacement data at critical locations. The algorithm is used to find the changes needed in the stiffnesses of the elements and the distribution of nonstructural mass of the nominal analytical model to correlate the analytical and experimental data. The algorithm alternates between the vibration analysis and static analysis to find the equivalent load vector and modify the stiffnesses. The identified stiffness properties of the structural elements can be used to control and study the dynamic response of the structure.     

A hybrid approach to constrained global optimization

In this paper, we propose a novel hybrid global optimization method to solve constrained optimization problems. An exact penalty function is first applied to approximate the original constrained optimization problem by a sequence of optimization problems with bound constraints. To solve each of these box constrained optimization problems, two hybrid methods are introduced, where two different strategies are used to combine limited memory BFGS (L-BFGS) with Greedy Diffusion Search (GDS). The convergence issue of the two hybrid methods is addressed. To evaluate the effectiveness of the proposed algorithm, 18 box constrained and 4 general constrained problems from the literature are tested. Numerical results obtained show that our proposed hybrid algorithm is more effective in obtaining more accurate solutions than those compared to.     

A Cooperative approach to particle swarm optimization

The particle swarm optimizer (PSO) is a stochastic, population-based optimization technique that can be applied to a wide range of problems, including neural network training. This paper presents a variation on the traditional PSO algorithm, called the cooperative particle swarm optimizer, or CPSO, employing cooperative behavior to significantly improve the performance of the original algorithm. This is achieved by using multiple swarms to optimize different components of the solution vector cooperatively. Application of the new PSO algorithm on several benchmark optimization problems shows a marked improvement in performance over the traditional PSO.     

A stochastic approach to hotel revenue optimization

Owning to similar business nature, it should be possible to directly migrate successful airline revenue management techniques to the hotel domain. However, one of the salient differences between airlines and hotels is rarely highlighted—the network structure of length of stay or the displacement effect. The hotel patrons go from a first stay-over night to a last stay-over night in consecutive night stays. The arrival demands for multi-night stays and the lengths of stay are stochastic in nature.In this paper, we propose a network optimization model for hotel revenue management under an uncertain environment. The network optimization is in a stochastic programming formulation so as to capture the randomness of the unknown demand (unknown number of arrivals and length of stays). A novel approach of robust optimization techniques for stochastic programming is applied to solve the problem. We also discuss the strategies for hotel management to take into account of risk trade-off; different pricing policies; cancellations and no-show; early check-outs; extended stay and over-booking are discussed. We showed that our proposed model can be modified to adopt these strategic considerations.     

A variable-complexity approach to second-order reliability-based optimization

This paper outlines a new methodology for second-order reliability-based optimization (RBO). A variable-complexity (VC) approach is used to implement a computationally efficient VCRBO algorithm, which reduces the number of costly second-order reliability analyses by using a lower fidelity, scaled mean-value technique during the majority of the constraint assessments. Two numerical examples are presented, which provide a comparison of several standard RBO approaches with the proposed algorithm. The examples include both Gaussian and non-Gaussian uncertainty to introduce significant nonlinearities in the limit state functions (LSFs). The design spaces and LSFs for both examples are presented, along with a discussion of the computational cost associated with the different RBO approaches.     

A convex optimization approach to the mode acceleration problem

The purpose of this note is to introduce an alternative procedure to the mode acceleration method when the underlying structure model includes damping. We will show that the problem can be cast as a convex optimization problem that can be solved via linear matrix inequalities.     

A simple approach to structural frequency optimization

This paper presents a simple solution strategy to find the shape and topology of a general structure that maximize or minimize the natural frequency. The structure is modelled with a fine mesh of finite elements. During an evolutionary process, a small part of the material is removed from the structure at the end of each finite element analysis. A criterion is established as to which elements should be eliminated so that the frequency of the resulting structure can be increased or reduced. It is found that the proposed simple method is effective in solving frequency optimization problems which usually require sophisticated mathematical programming techniques to solve.     

A graph theoretical approach to states and unitary operations

Quantum Information Processing - Building upon our previous work, on graphical representation of a quantum state by signless Laplacian matrix, we pose the following question. If a local unitary...     

A random set approach to the optimization of uncertain structures

The single-objective optimization of structures, whose parameters are assigned as fuzzy numbers or fuzzy relations, is presented in this paper as a particular case of the random set theory and evidence theory approach to uncertainty. Some basic concepts concerning these theories are reviewed and the relationships among interval analysis, convex modeling, possibility theory and probability theory are pointed out. In this context a frequentistic view of fuzzy sets makes sense and it is possible to calculate bounds on the probability that the solution satisfies the constraints. Some special but useful cases illustrate in detail the meaning of the approach proposed and its links with a recent formulation conceived within the context of convex modeling. Some theorems allow a very efficient computational procedure to be set up in many real design situations. Two numerical examples illustrate the model presented.     

A percentile system optimization approach with and without path enumeration

In this paper we deal with the travel time reliability PUE (probabilistic user equilibrium) problem studied by Lo et al. (2006) [12] and Nie (2011) [15] and we propose an alternative model that assumes a location-scale family for the path travel times, whose means and variances are evaluated in terms of link travel times. This avoids the use of the central limit theorem and convolutions providing a flexible and simple alternative. Contrary to the most existing models that require path enumeration or an iterative method to add paths sequentially, we present a percentile system optimization in its two versions: with and without path enumeration. Two examples of applications, one of them real, are used to illustrate the power of the proposed method. The cpu times required to solve the problem seem reasonable. In addition, we answer an open question raised by Nie (2011) [15] about the permutability of percentiles and partial derivatives of route travel times with respect to route flows. A family of counterexamples is given to demonstrate that the two operations: (a) obtain percentiles and (b) partial derivation of route travel times do not commute. Finally, to reproduce the trial-and-error sequence followed by users when selecting paths, we also present an algorithm that simulates this iterative process and shows that the final long-term user behavior coincides with PUE (probabilistic user equilibrium) problem resulting from some existing models.     

Toward a theoretical approach to medical error reporting system research and design

The release of the Institute of Medicine (Kohn et al., 2000) report "To Err is Human", brought attention to the problem of medical errors, which led to a concerted effort to study and design medical error reporting systems for the purpose of capturing and analyzing error data so that safety interventions could be designed. However, to make real gains in the efficacy of medical error or event reporting systems, it is necessary to begin developing a theory of reporting systems adoption and use and to understand how existing theories may play a role in explaining adoption and use. This paper presents the results of a 9-month study exploring the barriers and facilitators for the design of a statewide medical error reporting system and discusses how several existing theories of technology acceptance, adoption and implementation fit with many of the results. In addition we present an integrated theoretical model of medical error reporting system design and implementation.     

A unified quadratic-programming-based dynamical system approach to joint torque optimization of physically constrained redundant manipulators

In this paper, for joint torque optimization of redundant manipulators subject to physical constraints, we show that velocity-level and acceleration-level redundancy-resolution schemes both can be formulated as a quadratic programming (QP) problem subject to equality and inequality/bound constraints. To solve this QP problem online, a primal-dual dynamical system solver is further presented based on linear variational inequalities. Compared to previous researches, the presented QP-solver has simple piecewise-linear dynamics, does not entail real-time matrix inversion, and could also provide joint-acceleration information for manipulator torque control in the velocity-level redundancy-resolution schemes. The proposed QP-based dynamical system approach is simulated based on the PUMA560 robot arm with efficiency and effectiveness demonstrated.     

Principles of work system performance optimization: A business ergonomics approach

Recently, there has been a growing interest in optimizing performance in the workplace. This interest is stimulated not only by economic and competitive pressures, but also by a growing awareness of the need to improve health and safety, thereby improving workplace wellness and vitality and, in turn, productivity. This article reviews the contributions of traditional approaches to work system performance optimization. These approaches include scientific management, work-time studies, industrial psychology, ergonomics, human factors, industrial engineering, total quality management, kaizen theory, systems theory, and operations research. The benefits, features, and drawbacks of each approach are discussed and tabulated. A basis for a new comprehensive methodology of work system performance optimization called the business ergonomics approach is then outlined and presented. © 1999 John Wiley & Sons, Inc.     

A hyper-heuristic approach to aircraft structural design optimization

The conceptual design of an aircraft is a challenging problem in which optimization can be of great importance to the quality of design generated. Mass optimization of the structural design of an aircraft aims to produce an airframe of minimal mass whilst maintaining satisfactory strength under various loading conditions due to flight and ground manoeuvres. Hyper-heuristic optimization is an evolving field of research wherein the optimization process is continuously adapted in order to provide greater improvements in the quality of the solution generated. The relative infancy of hyper-heuristic optimization has resulted in limited application within the field of aerospace design. This paper describes a framework for the mass optimization of the structural layout of an aircraft at the conceptual level of design employing a novel hyper-heuristic approach. This hyper-heuristic approach encourages solution space exploration, thus reducing the likelihood of premature convergence, and improves the feasibility of and convergence upon the best solution found. A case study is presented to illustrate the effects of hyper-heuristics on the problem for a large commercial aircraft. Resulting solutions were generated of considerably lighter mass than the baseline aircraft. A further improvement in solution quality was found with the use of the hyper-heuristics compared to that obtained without, albeit with a penalty on computation time.