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

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

Over the past decades, the Multicommodity Network Flow (MCNF) problem has grown popular in the academic literature and a growing number of researchers are interested in this field. It is a powerful operational research approach to tackle and solve many complicated problems, especially in transportation and telecommunication contexts. Yet, few literature reviews have made an effort to classify the existing articles accordingly. In this article, we present a taxonomic review of the MCNF literature published between 2000 and 2019. Based on an adapted version of an existing comprehensive taxonomy, we have classified 263 articles into two main categories of applications and solution methods. We have also analyzed the research interests in the MCNF literature. This classification is the first to categorize the articles into this level of detail. Results show that there are topics, which need to be addressed in future researches.

The multicommodity network flow problem: state of the art classification, applications, and solution methods

A well designed train timetable should fully utilize the limited infrastructure and rolling stock resources to maximize operators’ profits and passenger travel demand satisfaction. Thus, an internally coherent scheduling process should consider the three main aspects: (1) dynamic choice behaviors of passengers so as to evaluate and calculate the impact of variable passenger demand to (2) underlying train service patterns and detailed timetables, which in turn are constrained by (3) infrastructure and rolling stock capacity. This paper aims to develop an integrated demand/service/resource optimization model for managing the above-mentioned three key decision elements with a special focus on passengers’ responses to time-dependent service interval times or frequencies. The model particularly takes into account service-sensitive passenger demand as internal variables so that one can accurately map passengers to train services through a representation of passenger carrying states throughout a team of trains. The added state dimension leads to a linear integer multi-commodity flow formulation in which three closely interrelated decision elements, namely passengers’ response to service interval times, train stopping pattern planning and timetabling for conflict detecting and resolving are jointly considered internally. By using a Lagrangian relaxation solution framework to recognize the dual costs of both passenger travel demand and limited resources of track and rolling stock, we transfer and decompose the formulation into a novel team-based train service search sub-problem for maximizing the profit of operators. The sub-problem is solvable efficiently by a forward dynamic programming algorithm across multiple trains of a team. Numerical experiments are conducted to examine the efficiency and effectiveness of the dual and primal solution search algorithms.

An integrated train service plan optimization model with variable demand: A team-based scheduling approach with dual cost information in a layered network

The engineering and business problems the world faces today have become more impenetrable and unstructured, making the design of a satisfactory problem-specific algorithm nontrivial.Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends is a collection of the latest developments, models, and applications within the transdisciplinary fields related to metaheuristic computing. Providing researchers, practitioners, and academicians with insight into a wide range of topics such as genetic algorithms, differential evolution, and ant colony optimization, this book compiles the latest findings, analysis, improvements, and applications of technologies within metaheuristic computing.

Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends

Multicommodity Network Design Problem in Rail Freight Transportation Planning

The fixed-cost Capacitated Multicommodity Network Design (CMND) problem is a well known NP-hard problem This paper presents a matheuristic algorithm combining Simulated Annealing (SA) metaheuristic and Simplex method for CMND problem In the proposed algorithm, a binary array is considered as solution representation and the SA algorithm manages open and closed arcs Several strategies for opening and closing arcs are proposed and evaluated In this matheuristic approach, for a given design vector, CMND becomes a Capacitated Multicommodity minimum Cost Flow (CMCF) problem The exact evaluation of the CMCF problem is performed using the Simplex method The parameter tuning for the proposed algorithm is done by means of design of experiments approach The performance of the proposed algorithm is evaluated by solving different benchmark instances The results of the proposed algorithm show that it is able to obtain better solutions in comparison with previous methods in the literature

A Hybrid Simulated Annealing and Simplex Method for Fixed-Cost Capacitated Multicommodity Network Design

Reengineering the Locomotive Operation Management Process in the Railways of Iran (RAI)

Metaheuristic algorithms will gain more and more popularity in the future as optimization problems are increasing in size and complexity. In order to record experiences and allow project to be replicated, a standard process as a methodology for designing and implementing metaheuristic algorithms is necessary. To the best of the authors' knowledge, no methodology has been proposed in literature for this purpose. This paper presents a Design and Implementation Methodology for Metaheuristic Algorithms, named DIMMA. The proposed methodology consists of three main phases and each phase has several steps in which activities that must be carried out are clearly defined in this paper. In addition, design and implementation of tabu search metaheuristic for travelling salesman problem is done as a case study to illustrate applicability of DIMMA.

DIMMA: A Design and Implementation Methodology for Metaheuristic Algorithms-A Perspective from Software Development

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Multicommodity Network Design Problem in Rail Freight Transportation Planning

A Hybrid Simulated Annealing and Simplex Method for Fixed-Cost Capacitated Multicommodity Network Design

Reengineering the Locomotive Operation Management Process in the Railways of Iran (RAI)

DIMMA: A Design and Implementation Methodology for Metaheuristic Algorithms-A Perspective from Software Development