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Full Description
This
textbook approaches optimization from a multi-aspect, multi-criteria perspective.
By using a Multiple Criteria Decision Making (MCDM) approach, it avoids the
limits and oversimplifications that can come with optimization models with one
criterion. The book is presented in a concise form, addressing how to solve decision
problems in sequences of intelligence, modelling, choice and review phases,
often iterated, to identify the most preferred decision variant. The approach
taken is human-centric, with the user taking the final decision is a sole and
sovereign actor in the decision making process. To ensure generality, no
assumption about the Decision Maker preferences or behavior is made. The presentation
of these concepts is illustrated by numerous examples, figures, and problems to
be solved with the help of downloadable spreadsheets. This electronic
companion contains models of problems to be solved built in Excel spreadsheet
files.
Optimization
models are too often oversimplifications of decision problems met in practice.
For instance, modeling company performance by an optimization model in which
the criterion function is short-term profit to be maximized, does not fully
reflect the essence of business management. The company's managing staff is
accountable not only for operational decisions, but also for actions which
shall result in the company ability to generate a decent profit in the future.
This calls for management decisions and actions which ensure short-term
profitability, but also maintaining long-term relations with clients,
introducing innovative products, financing long-term investments, etc. Each of
those additional, though indispensable actions and their effects can be modeled
separately, case by case, by an optimization model with a criterion function
adequately selected. However, in each case the same set of constraints
represents the range of company admissible actions. The aim and the scope of
this textbook is to present methodologies and methods enabling modeling of such
actions jointly.
Contents
Introduction.- Solving Decision Problems.- Decision Problem: Selection of a Single Variant.- Derivation of Efficient Variants.- Decision Problem: Selection of a Variant Portfolio - The Discrete Case.- Decision Problem: Selection of a Variant Portfolio - The Continuous Case.- Derivation of Efficient Portfolios.- Supporting the Process of the Most Preferred Variant Choice.- Decision Problems - Continuation.- Decision Problem: Selection of a Stock Portfolio.- Relations.
