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

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Artificial neural networks

Introduction to stochastic programming

https://ira.lib.polyu.edu.hk/bitstream/10397/1269/1/SetupSurvey-2006%28June-19%29.pdf

A survey of scheduling problems with setup times or costs

Lot sizing is one of the most important and also one of the most difficult problems in production planning. This subject has been studied extensively in the literature. In this article, we consider single-level lot sizing problems, their variants and solution approaches. After introducing factors affecting formulation and the complexity of production planning problems, and introducing different variants of lot sizing and scheduling problems, we discuss single-level lot sizing problems, together with exact and heuristic approaches for their solution. We conclude with some suggestions for future research.

/pdf/the-capacitated-lot-sizing-problem-a-review-of-models-and-4w6zf77n9a.pdf

The capacitated lot sizing problem: a review of models and algorithms

An immune algorithm approach to hybrid flow shops scheduling with sequence-dependent setup times

A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times, sequence-dependent setup times and learning effect

Research highlights? Integrated flexible job-shop and preventive maintenance is probed in this study. ? Makespan as an objective for production part and reliability as an objective for maintenance part are optimized simultaneously. ? A mathematic model and a solving method are introduced in this paper and results are compared carefully. This paper investigates integrated flexible job shop problem (FJSP) with preventive maintenance (PM) activities under the multi-objective optimization approaches. Finding compromise solutions between the production objectives and maintenance ones is under consideration. In order to carry out the maintenance activities, reliability models are employed. This paper attempts to simultaneously optimize two objectives: the minimization of the makespan for the production part and the minimization of the system unavailability for the maintenance part. For doing it so, two decisions are taken at the same time: finding the appropriate assignment of n jobs on m machines in order to minimize the makespan and deciding when to execute the PM activities in order to minimize the system unavailability. Both the maintenance activity numbers and maintenance intervals are not fixed in advance. Four multi-objective optimization methods are compared to find the Pareto-optimal front in the flexible job-shop problem case. Promising the obtained results, a benchmark with a large number of test instances (more than 4800) and meticulous care is employed.

Bi-objective optimization research on integrated fixed time interval preventive maintenance and production for scheduling flexible job-shop problem

Cross-docking is an approach in inventory management which can reduce inventories, lead times and customer response time. In this strategy, products and shipments are unloaded from inbound trucks, sorted and categorized based on their characteristics, moved and loaded onto outbound trucks for delivery to demand points in a distribution network. The important fact is that, the items are stored in the inventory for a period which is primarily less than the actual time allocated to keep these items in a typical warehouse. Therefore, total cost and space requirement for inventory can be cut down. One of the most important targets in such systems is to establish coordination between the performance of inbound and outbound trucks in that these trucks can be scheduled, and the product items can be allocated to trucks effectively. This paper addresses some meta-heuristics to find the best sequence of inbound and outbound trucks, so that the objective, minimizing the total operation time called makespan, can be satisfied. Furthermore, not only the efficiency and capability of the algorithms' parameters are assessed and analyzed by some performance measures, but also these meta-heuristics are compared with each other in order to find out the set of homogeneous algorithms among all proposed algorithms. By this analysis, it can be shown that the suitability of these meta-heuristics is quite sensible especially for the cross-docking systems with large sizes in which a high volume of inbound or outbound trucks transmit the product items.

S. M. T. Fatemi Ghomi

Papers

The capacitated lot sizing problem: a review of models and algorithms

An immune algorithm approach to hybrid flow shops scheduling with sequence-dependent setup times

A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times, sequence-dependent setup times and learning effect

Bi-objective optimization research on integrated fixed time interval preventive maintenance and production for scheduling flexible job-shop problem

Meta-heuristics implementation for scheduling of trucks in a cross-docking system with temporary storage