Under intense scrutiny for the last few decades, Multiple
Objective Decision Making (MODM) has been useful for dealing with
the multiple-criteria decisions and planning problems associated
with many important applications in fields including management
science, engineering design, and transportation. Rough set theory
has also proved to be an effective mathematical tool to counter the
vague description of objects in fields such as artificial
intelligence, expert systems, civil engineering, medical data
analysis, data mining, pattern recognition, and decision
theory.
Rough Multiple Objective Decision Making is perhaps the first
book to combine state-of-the-art application of rough set theory,
rough approximation techniques, and MODM. It illustrates
traditional techniques-and some that employ simulation-based
intelligent algorithms-to solve a wide range of realistic problems.
Application of rough theory can remedy two types of uncertainty
(randomness and fuzziness) which present significant drawbacks to
existing decision-making methods, so the authors illustrate the use
of rough sets to approximate the feasible set, and they explore use
of rough intervals to demonstrate relative coefficients and
parameters involved in bi-level MODM. The book reviews relevant
literature and introduces models for both random and fuzzy rough
MODM, applying proposed models and algorithms to problem
solutions.
Given the broad range of uses for decision making, the authors
offer background and guidance for rough approximation to real-world
problems, with case studies that focus on engineering applications,
including construction site layout planning, water resource
allocation, and resource-constrained project scheduling. The text
presents a general framework of rough MODM, including basic theory,
models, and algorithms, as well as a proposed methodological system
and discussion of future research.
General
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