THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Aquila Optimizer: A novel meta-heuristic optimization algorithm

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.

/pdf/a-comprehensive-survey-on-particle-swarm-optimization-1d380v5xx1.pdf

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

The Federal Aviation Administration (FAA), with its NextGen Air Transportation System (NextGen) and Performance-Based Navigation (PBN) initiatives, is moving towards a concept of integrated procedures implementation. Performance-Based Navigation initiatives include implementing Area Navigation (RNAV) and Required Navigation Performance (RNP) routes and procedures. The integrative concept of implementation of these procedures would mean a migration away from site by site (or runway by runway) procedure implementation process towards a NextGen readiness concept. This concept will include development of an integrated system of PBN routes and procedures by geographic area (incorporating metro areas and outlying airports). This concept delivers optimum benefits for the air traffic and carrier community. In addition, the integrative approach helps in prioritizing and formulating the funding requests to combine airspace, environmental, and procedures development. This paper discusses different aspects of this integrative approach.

http://ieeexplore.ieee.org/iel5/5165450/5172820/05172877.pdf

Integrated approach

Software Defined Networking (SDN) marks a paradigm shift towards an externalized and logically centralized network control plane. A particularly important task in SDN architectures is that of controller placement, i.e., the positioning of a limited number of resources within a network to meet various requirements. These requirements range from latency constraints to failure tolerance and load balancing. In most scenarios, at least some of these objectives are competing, thus no single best placement is available and decision makers need to find a balanced trade-off. This work presents POCO, a framework for Pareto-based Optimal COntroller placement that provides operators with Pareto optimal placements with respect to different performance metrics. In its default configuration, POCO performs an exhaustive evaluation of all possible placements. While this is practically feasible for small and medium sized networks, realistic time and resource constraints call for an alternative in the context of large scale networks or dynamic networks whose properties change over time. For these scenarios, the POCO toolset is extended by a heuristic approach that is less accurate, but yields faster computation times. An evaluation of this heuristic is performed on a collection of real world network topologies from the Internet Topology Zoo. Utilizing a measure for quantifying the error introduced by the heuristic approach allows an analysis of the resulting trade-off between time and accuracy. Additionally, the proposed methods can be extended to solve similar virtual functions placement problems which appear in the context of Network Functions Virtualization (NFV).

Heuristic Approaches to the Controller Placement Problem in Large Scale SDN Networks

Today’s fierce competition demands an enterprise solution that could integrate all functional parts of an organizations and subsequently disseminate the necessary data to the managers. Despite numerous implementation cases of such total solutions around the globe, it is still an excruciating and risky practice to embed corresponding solutions into a new case. Our paper presents a unique experience of development and deployment of a customized solution in a specific circumstance whose high rate of failure in the implementation phase has been emphasized by previous studies. To embody the sense of adventure, the paper structure is laid out based on the narrative arc of story-telling approach. It starts with providing an exposition and enumerating the rising actions as well as introducing the hero who incites the incident. The paper continues with elaborating the major crisis faced during on implementing such a solution while marking a thrilling climax of surmounting the challenges. Finally, it leads to a happy denouement since a complementary project associated with that enterprise solution is ordered to be accomplished by the hero.

http://journal.research.fanap.com/article_103704_31b6046d5f4224b3fac57b5ec951625b.pdf

An Enterprise Solution in Practice: Issues and Challenges

Resource constrained scheduling problem (RCPSP) Net present value Fuzzy set theory Vibration Damping Optimization (VDO) Simulated Annealing (SA) Resource-constrained project scheduling problem (RCPSP) aims to schedule at minimal duration a set of activities subject to precedence constraints and the limited availability of resources. Considering net present value (NPV) is one of the modern approaches in scheduling projects in which the project is scheduled in such a way that NPV be maximized. This approach with deterministic parameters such as activities duration was analyzed in the previous works. Since estimating the activities duration in exact manner is far from reality, we utilize an approximate estimation approach in scheduling project under fuzzy environment. In this respect, earliest start times and latest finish times for activities considered as fuzzy numbers. Since the problem is NP-hard problem, a novel meta-heuristic called vibration damping optimization (VDO) is proposed to solve the mathematical model. To demonstrate performance of proposed VDO, simulated anneling algorithm is applied. We also applied bi-directional scheduling method in order to generate neighborhoods. The result shows that the proposed VDO is capable to solve the model.

http://ijiepm.iust.ac.ir/article-1-1369-fa.pdf

A Vibration Damping Optimization TO Maximize Net Present Value for Resource Constrained Project Scheduling Problem

In the modern era, information technology-based solution providers are encountering a growing request for satisfying the versatile requirements of their customers in terms of software applications. To this end, specific approaches have been designed to streamline the way of accomplishing software projects in an efficient manner, i.e., agile-oriented frameworks. Even though previous studies have highlighted variations of such a framework, the literature has not addressed the adaptations required in response to the gradual maturity of a wide-ranging case study dealing with software applications. Following a case study-oriented methodology, this paper focuses on elaborating a set of workable maneuvers to mature the Scrum framework when applied to portfolio management. Particularly, we highlight how Scrum should be adapted from its basic setting to a vision and goal-oriented configuration or Scrumban under certain conditions. As a maturing practice, we propose a heuristic scoring technique to determine the sprint length of subprojects with different characteristics in the context of a portfolio. The study also introduces a multi-level refinement structure to enhance the monitoring of the teams’ performance under the proposed mature framework. The results obtained display a considerable spike in the realization rate of release planning in light of the actual performance.

Maturing the Scrum Framework for Software Projects Portfolio Management: A Case Study-Oriented Methodology

Flow shop scheduling deals with the determination of the optimal sequence of jobs processing on machines in a fixed order with the main objective consisting of minimizing the completion time of all jobs (makespan). This type of scheduling problem appears in many industrial and production planning applications. This study proposes a new bi-objective mixed-integer programming model for solving the synchronous flow shop scheduling problems with completion time. The objective functions are the total makespan and the sum of tardiness and earliness cost of blocks. At the same time, jobs are moved among machines through a synchronous transportation system with synchronized processing cycles. In each cycle, the existing jobs begin simultaneously, each on one of the machines, and after completion, wait until the last job is completed. Subsequently, all the jobs are moved concurrently to the next machine. Four algorithms, including non-dominated sorting genetic algorithm (NSGA II), multi-objective simulated annealing (MOSA), multi-objective particle swarm optimization (MOPSO), and multi-objective hybrid vibration-damping optimization (MOHVDO), are used to find a near-optimal solution for this NP-hard problem. In particular, the proposed hybrid VDO algorithm is based on the imperialist competitive algorithm (ICA) and the integration of a neighborhood creation technique. MOHVDO and MOSA show the best performance among the other algorithms regarding objective functions and CPU Time, respectively. Thus, the results from running small-scale and medium-scale problems in MOHVDO and MOSA are compared with the solutions obtained from the epsilon-constraint method. In particular, the error percentage of MOHVDO’s objective functions is less than 2% compared to the epsilon-constraint method for all solved problems. Besides the specific results obtained in terms of performance and, hence, practical applicability, the proposed approach fills a considerable gap in the literature. Indeed, even though variants of the aforementioned meta-heuristic algorithms have been largely introduced in multi-objective environments, a simultaneous implementation of these algorithms as well as a compared study of their performance when solving flow shop scheduling problems has been so far overlooked. 

A bi-objective hybrid vibration damping optimization model for synchronous flow shop scheduling problems

Urban vulnerability is the probability of damage to cities and urban infrastructures against natural and unnatural events. In this regard, in the last half century, land subsidence has involved many countries as a potential risk for urban, industrial and agricultural areas. With the occurrence of land subsidence, the physical and structural characteristics of the structures built in the city are changed and show different behavior. For this reason, it is important to consider the effect of land subsidence on the urban fabric in which there are exposed and buried structures. The involvement of the 17th district of Tehran with the issue of land subsidence was the initial idea of the current research. Currently, the maximum land subsidence rate in this area is 25 cm per year. The present research has been carried out in the form of spatial studies and by implementing the analytical model in four steps. The results of the model implementation showed that the urban fabric of the 17th district is prone to high vulnerability due to features such as high population and building density, the presence of worn-out fabric, buildings with low structural strength and very low construction quality of buildings. In total, about 657 hectares (80 percent) of the built-up lands in the 17th district of Tehran are under the influence of land subsidence.

/pdf/measuring-the-vulnerability-of-the-urban-fabric-in-the-face-1g8m5znd.pdf

Vahid Hajipour

Papers

An Enterprise Solution in Practice: Issues and Challenges

A Vibration Damping Optimization TO Maximize Net Present Value for Resource Constrained Project Scheduling Problem

Maturing the Scrum Framework for Software Projects Portfolio Management: A Case Study-Oriented Methodology

A bi-objective hybrid vibration damping optimization model for synchronous flow shop scheduling problems

Measuring the Vulnerability of the Urban Fabric in the Face of Land Subsidence (Case Study: District 17 of Tehran)