(1975). The Limits of Organization. Journal of Economic Issues: Vol. 9, No. 3, pp. 543-544.

The Limits of Organization

The fifth edition of "Numerical Methods for Engineers" continues its tradition of excellence. Instructors love this text because it is a comprehensive text that is easy to teach from. Students love it because it is written for them--with great pedagogy and clear explanations and examples throughout. The text features a broad array of applications, including all engineering disciplines. The revision retains the successful pedagogy of the prior editions. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation, preparing the student for what is to come in a motivating and engaging manner. Each part closes with an Epilogue containing sections called Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods. Approximately 80% of the end-of-chapter problems are revised or new to this edition. The expanded breadth of engineering disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical engineering. Users will find use of software packages, specifically MATLAB and Excel with VBA. This includes material on developing MATLAB m-files and VBA macros.

Numerical methods for engineers

We consider heuristic algorithms for the resource-constrained project scheduling problem. Starting with a literature survey, we summarize the basic components of heuristic approaches. We briefly describe so-called X -pass methods which are based on priority rules as well as metaheuristic algorithms. Subsequently, we present the results of our in-depth computational study. Here, we evaluate the performance of several state-of-the-art heuristics from the literature on the basis of a standard set of test instances and point out to the most promising procedures. Moreover, we analyze the behavior of the heuristics with respect to their components such as priority rules and metaheuristic strategy. Finally, we examine the impact of problem characteristics such as project size and resource scarceness on the performance.

Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem

This paper reviews the research and development works conducted over the past few decades on carbon fiber reinforced metal matrix composites (CFR-MMC). The structure and composition of carbon fiber and its bonding to metal matrix have an impact on the properties of the resulting CFR-MMC remarkably. The research efforts on process optimization and utilizing of carbon fibers are discussed in this review. The effect of carbon fiber on structural, physical and mechanical properties of metal matrix composite are studied as well. This review also provide an overview of the research to date on various fabrication methods that is used for production of CFR-MMC.

Carbon fiber reinforced metal matrix composites: Fabrication processes and properties

The review presents a survey of the literature on structure–property relationships in epoxy-clay nanocomposites. Herein, various pivotal parameters affecting structures and properties of the nanocomposites including various types of modification as well as a vast range of available dispersion techniques were discussed. Opportunities and challenges in regards to potential applications of nanoclay in multi-scale composites have been also addressed. The multi-scale composites containing nanoclays have been reviewed in terms of mechanical properties in both out-of-plane and in-plane directions, and compared with those containing carbon based nanofillers. In this regards, the improving mechanisms in mechanical properties of both epoxy-clay nanocomposites and nanoclay filled fiber reinforced composites were also discussed.

A technical review on epoxy-clay nanocomposites: Structure, properties, and their applications in fiber reinforced composites

A competitive magnet-based genetic algorithm for solving the resource-constrained project scheduling problem

Thermal stabilization process of polyacrylonitrile (PAN) is the slowest and the most energy-consuming step in carbon fiber production. As such, in industrial production of carbon fiber, this step is considered as a major bottleneck in the whole process. Stabilization process parameters are usually many in number and highly constrained, leading to high uncertainty. The goal of this paper is to study and analyze the carbon fiber thermal stabilization process through presenting several effective dynamic models for the prediction of the process. The key point with using dynamic models is that using an evolutionary search technique, the heat of reaction can be optimized. The employed components of the study are Levenberg–Marquardt algorithm (LMA)-neural network (LMA-NN), Gauss–Newton (GN)-curve fitting, Taylor polynomial method, and a genetic algorithm. The results show that the procedure can effectively optimize a given PAN fiber heat of reaction based on determining the proper values of heating ramp and temperature.

Dynamic Prediction Models and Optimization of Polyacrylonitrile (PAN) Stabilization Processes for Production of Carbon Fiber

This paper introduces an admissible heuristic search algorithm — Search and Learning Algorithm (SLA*). SLA* is developed from the work presented by Korf in the Learning-Real-Time-Algorithm (LRTA*). We retain the major elements of Korfs work in LRTA*, and improve its performance by incorporating a review component to fully reflect the effect the learning of new heuristic from front states has upon the previous states. The combined strategy of search, learning, and review has enabled this algorithm to accumulate knowledge continuously through guided expansion, and to identify better search directions in any stage of nodes expansion. With the assumption of non-overestimating initial estimates for all nodes to the goal, this algorithm is able to find an optimal solution in a single problem solving trial with good efficiency. We provide a proof for the optimality of the solution.

An Admissible Heuristic Search Algorithm

Embedding learning capability in Lagrangean relaxation: An application to the travelling salesman problem

Ionic polymer conductive network composite (IPCNC) actuators are a class of electroactive polymer composites that exhibit some interesting electromechanical characteristics such as low voltage actuation, large displacements, and benefit from low density and elastic modulus. Thus, these emerging materials have potential applications in biomimetic and biomedical devices. Whereas significant efforts have been directed toward the development of IPMC actuators, the establishment of a proper mathematical model that could effectively predict the actuators’ dynamic behavior is still a key challenge. This paper presents development of an effective modeling strategy for dynamic analysis of IPCNC actuators undergoing large bending deformations. The proposed model is composed of two parts, namely electrical and mechanical dynamic models. The electrical model describes the actuator as a resistive-capacitive (RC) transmission line, whereas the mechanical model describes the actuator as a system of rigid links connected by spring-damping elements. The proposed modeling approach is validated by experimental data, and the results are discussed.

Reza Zamani

Papers

A competitive magnet-based genetic algorithm for solving the resource-constrained project scheduling problem

Dynamic Prediction Models and Optimization of Polyacrylonitrile (PAN) Stabilization Processes for Production of Carbon Fiber

An Admissible Heuristic Search Algorithm

Embedding learning capability in Lagrangean relaxation: An application to the travelling salesman problem

Nonlinear dynamic modeling of ionic polymer conductive network composite actuators using rigid finite element method