International Series in Management Science Operations Research – serie

1. 1. Motivation This book is based on the view-tx)int that both public and private decision making, in practice, can often be ilrproved upon by means of fonnal (nonnative) decision nodels and methods. To sane extent, the validity of this statement can be measured by the irrpressive number of su=esses of disciplines as operations research and management science. Hcwever, as witnessed by the many discussions in the professional journals in these fields, many rrodels and methods do not completely meet the requirements of decision making in prac- tice. Of all possible origins of these clear shortcomings, we main-* ly focus on only one: the fact that nost of these nodels and methods are unsuitable for decision situations in which multiple and possi- bly conflicting objectives playa role, because they are concentra- ted on the (optimal) fulfilment of only one objective. The need to account for multiple goals was observed relatively early. Hoffman [1955], while describing 'what seem to be the prin- cipal areas (in linear prograrrrning) where new ideas and new methods are needed' gives an exanple with conflicting goals.In this pro- blem, the assignrrent of relative weights is a great problem for the planning staff and is 'probably not the province of the mathemati- cian engaged in solving this problem'. These remarks were true pre- cursors of later develor:nents. Nevertheless, the need for methods dealing with multiple goals was not widely recognized until much later.

This book presents applications of the Analytic Hierarchy Process developed by Thomas L. Saaty to deal with unstructured decision problems, together with case histories developed by him and in collaboration with others in areas of current societal concern. Its purpose is to provide the reader with examples of how to deal with unstructured problems, particularly ones involving socio­ economic and political issues with qualitative and intangible factors. These examples show how to use judgment and experience to analyze a com­ plex decision problem by combining its qualitative and quantitative aspects in a single framework and generating a set of priorities for alternative courses of action. The process has inherent flexibilities in structuring a problem and in taking diverse judgments from people, whether singly, in a group working together, or by questionnaire. Decisionmakers will profit from this approach. It makes accessible to them a framework for understanding the complexity of the system they are in as it impinges on the surrounding environment. To deal with complexity, we must first understand it. Systems thinking is necessary if all the important factors are to be considered. Complex systems problems can challenge and tax our logical capability to fully understand their causes and the consequences of any action we may take to solve them. Neverthe­ less, in time their effects on us tend to become better known than their causes.

In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech­ niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decision making, logic, operations research, pattern recognition, robotics and others, provide an affirmative answer to this question. In spite of the large number of publications, good and comprehensive textbooks which could facilitate the access of newcomers to this area and support teaching were missing until recently. To help to close this gap and to provide a textbook for courses in fuzzy set theory which can also be used as an introduction to this field, the first volume ofthis book was published in 1985 [Zimmermann 1985 b]. This volume tried to cover fuzzy set theory and its applications as extensively as possible. Applications could, therefore, only be described to a limited extent and not very detailed.

1. 1. Motivation This book is based on the view-tx)int that both public and private decision making, in practice, can often be ilrproved upon by means of fonnal (nonnative) decision nodels and methods. To sane extent, the validity of this statement can be measured by the irrpressive number of su=esses of disciplines as operations research and management science. Hcwever, as witnessed by the many discussions in the professional journals in these fields, many rrodels and methods do not completely meet the requirements of decision making in prac- tice. Of all possible origins of these clear shortcomings, we main-* ly focus on only one: the fact that nost of these nodels and methods are unsuitable for decision situations in which multiple and possi- bly conflicting objectives playa role, because they are concentra- ted on the (optimal) fulfilment of only one objective. The need to account for multiple goals was observed relatively early. Hoffman [1955], while describing 'what seem to be the prin- cipal areas (in linear prograrrrning) where new ideas and new methods are needed' gives an exanple with conflicting goals.In this pro- blem, the assignrrent of relative weights is a great problem for the planning staff and is 'probably not the province of the mathemati- cian engaged in solving this problem'. These remarks were true pre- cursors of later develor:nents. Nevertheless, the need for methods dealing with multiple goals was not widely recognized until much later.

In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech­ niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decision making, logic, operations research, pattern recognition, robotics and others, provide an affirmative answer to this question. In spite of the large number of publications, good and comprehensive textbooks which could facilitate the access of newcomers to this area and support teaching were missing until recently. To help to close this gap and to provide a textbook for courses in fuzzy set theory which can also be used as an introduction to this field, the first volume ofthis book was published in 1985 [Zimmermann 1985 b]. This volume tried to cover fuzzy set theory and its applications as extensively as possible. Applications could, therefore, only be described to a limited extent and not very detailed.

Mass productio!l and mass consumption, so far considered virtues in a free economic soceity, have changed. Various problems have occurred including economic stagnation, energy crisis, shortage of material resources, prolifera­ tion of pollution, lack of skilled labor, rapid changes of product design, technical innovation, and others. Moreover, individual manufacturing firms must take steps to adopt multi-product, small-lot-sized (batch type) produc­ tion as a type of production in order to adapt themselves to a market movement characterized by a diversified and specialty-oriented society and a short product life cycle. The number of manufacturing firms worldwide that use a type of multi-product, small-lot-sized production is expected to increase. This is so even in the United States, which has been said to be a country of mass production. Multi-product, small-lot-sized production has been considered to be a milestone to flow-type mass production, which has been thought to be the most effective production system. Intensive efforts have been made to investigate mass production systems from both theoretical and practical viewpoints. Few studies have been made for multi-product, small-lot-sized production (batch-type manufacturing). Considering the present business circumstances faced with various difficulties, it is strongly required to establish some theories useful for making practically effective and flexible multi-product, small-lot-sized production systems. Several effective approaches to the batch-type manufacturing systems have been developed. Group technology (GT) is one such method that has steadily obtained great interest from progressive manufacturing firms all over the world.

The title of this book is Techniques in Corporate Manpower Planning: Methods and Applications. Manpower planning, also called personnel plan­ ning, implies the analysis of possible discrepancies in the future between personnel demand and supply. Personnel demand will also be called person­ nel requirement; and personnel supply, personnel availability. The notion of corporate manpower planning refers to the planning of personnel on the level of an industrial or governmental organization. As such, it does not stand for manpower planning for branches of industries or labor market studies of countries or international communities. One type of manpower planning is the planning of short-term succes­ sions of managers or the assignment planning of positions for individual employees for the next year. In fact, this type of short-term manpower plan­ ning is always executed, whether formally or informally, centrally or other­ wise. Another type of manpower planning, however, may be executed to match the requirement for and availability of personnel for the medium and long term. This type of manpower planning considers groups of employees rather than individuals. Our goal is to consider medium- and long-term manpower planning for groups of employees. We call this the multicategory vii Vlll PREFACE approach to manpower planning. In our view, this medium-and long-term personnel planning provides the conditions for individual manpower plan­ ning or for personnel development.