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

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

List of Figures. List of Tables. Preface. Foreword. 1. Basic Concepts. 2. Evolutionary Algorithm MOP Approaches. 3. MOEA Test Suites. 4. MOEA Testing and Analysis. 5. MOEA Theory and Issues. 3. MOEA Theoretical Issues. 6. Applications. 7. MOEA Parallelization. 8. Multi-Criteria Decision Making. 9. Special Topics. 10. Epilog. Appendix A: MOEA Classification and Technique Analysis. Appendix B: MOPs in the Literature. Appendix C: Ptrue & PFtrue for Selected Numeric MOPs. Appendix D: Ptrue & PFtrue for Side-Constrained MOPs. Appendix E: MOEA Software Availability. Appendix F: MOEA-Related Information. Index. References.

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Evolutionary algorithms for solving multi-objective problems

行銷硏究 : Marketing research

Economic Control of Quality of Manufactured Product.

In Chaps. 3 and 4, mathematical models have been proposed for the capacitated lot sizing problem with production carryover and setup crossover across periods. Heuristics based on both the mathematical models have also been proposed. The models and heuristics address real-life situations in process industries such as production immediately after setup and uninterrupted production carryover across periods.

Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover Across Periods Assuming Sequence-Dependent Setup Times and Setup Costs (CLSP-SD-PCSC): Mathematical Models for Process Industries

Generally, the CLSP addresses the production planning problem in discrete manufacturing industries and continuous manufacturing industries. A brief explanation about the production planning in discrete manufacturing industries and continuous manufacturing industries with relevant examples is presented in Sects. 2.1.1 and 2.1.2, respectively.

CLSP: Real Life Applications and Motivation to Study Lot Sizing Problems in Process Industries

This paper considers the Fixed-Charge Transportation Problem (FCTP), which spans multiple time periods and includes multiple stages, termed as Multi-Period, Multi-Stage Fixed-Charge Transportation Problem (MPMS-FCTP) in a supply chain. A generalised mathematical model which minimises the fixed and variable transportation, storage and backlog costs is proposed for the problem under study. Subsequently, two improved Lagrangian-Relaxation (LR)-based approaches are developed to efficiently solve the MPMS-FCTP. In addition, heuristics based on the improved LR approaches are proposed to obtain good upper bounds. The experimental results show that the proposed LR approaches perform better than the traditional LR approach with the sub-gradient optimisation. The lower bounds obtained using the proposed approaches are always non-decreasing in successive iterations of LR, providing tighter lower bounds. In addition, the proposed LR-based heuristics yield better solutions than the existing heuristics in the literature. Finally, the convergence to optimality of the proposed approaches is also discussed. 

Improved Lagrangian-relaxation based approaches for multi-period multi-stage fixed charge transportation problem

We consider a finite horizon Inventory Routing Problem in which the vendor monitors the inventory at the retailers and makes replenishment decisions for them. A single vendor manages several retailers who face deterministic but dynamic demands. The vendor decides the delivery schedule, delivery quantities, and vehicle routes that minimize the total supply chain cost. For practical purposes, we assume that split deliveries to a retailer are not allowed and that the backorders are allowed at the retailers. Two mixed integer linear programming models are proposed to solve the specified Inventory Routing Problem (IRP). Since IRP is NP-hard, two heuristics are also developed for the same problem. Numerical experiments were conducted on randomly generated data instances to evaluate the proposed models. The numerical study reveals that the proposed models are computationally efficient. We observed that the optimality gap of the solutions from the mathematical models was no more than 3% in all the tested cases. We also show that the proposed heuristics provide consistent near-optimal solutions. The proposed models and heuristics could serve as efficient decision-making tools to help supply chain managers make quick tactical level decisions.

Mathematical Models and Heuristics for an Inventory Routing Problem Without Split Deliveries

The shortest path problem is the problem of finding one-to-one path from the source to the destination. In real life, the problem involves conflicting and competing objectives, and many researchers solve the multiobjective shortest path optimization problem using a weighted linear combination of objectives. However, the solution of weighted sum is highly sensitive to the weights given, limiting the practicability of this method. Solving the problem by simultaneous optimization of the objective functions to generate a set of nondominated solutions can help to build a decision support system for travelers to choose their own path on the basis of their individual preferences. This chapter proposes a multiobjective mathematical model, solved using e-approach to obtain (heuristically) nondominated solutions of shortest paths with respect to time and distance. In this study, we consider minimizing both distance and time as the objective functions with real-life constraints such as time-dependent dynamic and deterministic travel times, time-dependent dynamic and deterministic waiting times, and time-dependent one-way traffic along the roads. We implement the proposed model by using the real-life planning data (1658 nodes and 4224 links) of Chennai city network (a metropolitan city in India with highly interconnected network of roads), and present the discussion on the multiobjective routing problem with real-life considerations.

Chandrasekharan Rajendran

Papers

Capacitated Lot Sizing Problem with Production Carryover and Setup Crossover Across Periods Assuming Sequence-Dependent Setup Times and Setup Costs (CLSP-SD-PCSC): Mathematical Models for Process Industries

CLSP: Real Life Applications and Motivation to Study Lot Sizing Problems in Process Industries

Improved Lagrangian-relaxation based approaches for multi-period multi-stage fixed charge transportation problem

Mathematical Models and Heuristics for an Inventory Routing Problem Without Split Deliveries

Multiobjective Routing in a Metropolitan City with Deterministic and Dynamic Travel and Waiting Times, and One-Way Traffic Regulation