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Current and former professional staff of the Population Council have updated the Handbook for Family Planning Operations Research Design. They assume that readers of the handbook already know terms and concepts of research design and statistics and have some field research experience. The primary objective of the manual is to provide guidance to health and family planning researchers to develop and write and detailed operations research proposal. In fact, it can be and has been used in workshops on research proposal writing. It also serves as a means for program administrators and managers to understand the workings of operations research and the application of research findings for improving service delivery. The authors draw from their field experiences from Asia, Africa, and Latin America. The handbook begins with a definition of operations research, its objectives, different types of operations research, and its desing. It guides readers on how to identify, define, and justify the research problem. Further it helps them to choose a strategy to solve the problem. I next covers objectives and hypotheses of the research. The handbook makes the readers aware of the need to describe the proposed intervention and to define variables and terms. It spends a considerable number of pages on study design including the different types of designs. It also provides guidance on sampling and data collection. The handbook gives detailed guidance on data tabulation and analysis. It also stresses the need to disseminate and use the research findings. It encourages researchers to list limitations of the study, resources, and facilities. It also addresses the preparation of appendixes, title page, and abstract.
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This proceedings volume contains selected and refereed contributions that were presented at the conference on "Recent Developments and New Perspectives of Operations Research in the Area of Production Planning and Control" in Hagen/Germany, 25. - 26. June 1992. This conference was organized with the cooperation of the FernuniversiHit Hagen and was jointly hosted by the "Deutsche Gesellschaft fur Operations Research (DGOR)" and the "Manufacturing Special Interest Group of the Operations Research Society of America (ORSA-SIGMA)". For the organization of the conference we received generous financial support from the sponsors listed at the end of this volume. We wish to express our appreciation to all supporters for their contributions. This conference was the successor of the JOInt ORSA/DGOR-conference in Gaithersburg/Maryland, USA, on the 30. and 31. July 1991. Both OR-societies committed themselves in 1989 to host joint conferences on special topics of interest from the field of operations research. This goal has been successfully realized in the area of production management; and it should be an incentive to conduct similar joint conferences on other topics of operations research in the years to come. The 36 contributions in this proceedings volume deal with general and special problems in production planning as well as approaches and algorithms for their solution. They cover a wide range of operations research within product management and will therefore address a wide circle of interested readers among OR-scientists and professionals alike.
A reference for those working at the interface of operations planning and optimization modeling, Operations Planning: Mixed Integer Optimization Models blends essential theory and powerful approaches to practical operations planning problems. It presents a set of classical optimization models with widespread application in operations planning. The
Sponsored by the Office for Industrial Associates of the California Institute of Technology and the Society for Morphological Research, Pasadena, California, May 22-24, 1967
The generalized area of multiple criteria decision making (MCDM) can be defined as the body of methods and procedures by which the concern for multiple conflicting criteria can be formally incorporated into the analytical process. MCDM consists mostly of two branches, multiple criteria optimization and multi-criteria decision analysis (MCDA). While MCDA is typically concerned with multiple criteria problems that have a small number of alternatives often in an environment of uncertainty (location of an airport, type of drug rehabilitation program), multiple criteria optimization is typically directed at problems formulated within a mathematical programming framework, but with a stack of objectives instead of just one (river basin management, engineering component design, product distribution). It is about the most modern treatment of multiple criteria optimization that this book is concerned. I look at this book as a nicely organized and well-rounded presentation of what I view as ”new wave” topics in multiple criteria optimization. Looking back to the origins of MCDM, most people agree that it was not until about the early 1970s that multiple criteria optimization c- gealed as a field. At this time, and for about the following fifteen years, the focus was on theories of multiple objective linear programming that subsume conventional (single criterion) linear programming, algorithms for characterizing the efficient set, theoretical vector-maximum dev- opments, and interactive procedures.
The scientific monograph of a survey kind presented to the reader's attention deals with fundamental ideas and basic schemes of optimization methods that can be effectively used for solving strategic planning and operations manage ment problems related, in particular, to transportation. This monograph is an English translation of a considerable part of the author's book with a similar title that was published in Russian in 1992. The material of the monograph embraces methods of linear and nonlinear programming; nonsmooth and nonconvex optimization; integer programming, solving problems on graphs, and solving problems with mixed variables; rout ing, scheduling, solving network flow problems, and solving the transportation problem; stochastic programming, multicriteria optimization, game theory, and optimization on fuzzy sets and under fuzzy goals; optimal control of systems described by ordinary differential equations, partial differential equations, gen eralized differential equations (differential inclusions), and functional equations with a variable that can assume only discrete values; and some other methods that are based on or adjoin to the listed ones.