Theory of fuzzy integrals and its applications

This paper will present a novel concept of expected values of fuzzy variables, which is essentially a type of Choquet integral and coincides with that of random variables. In order to calculate the expected value of general fuzzy variable, a fuzzy simulation technique is also designed. Finally, we construct a spectrum of fuzzy expected value models, and integrate fuzzy simulation, neural network, and genetic algorithms to produce a hybrid intelligent algorithm for solving general fuzzy expected value models.

Expected value of fuzzy variable and fuzzy expected value models

Real-life decisions are usually made in the state of uncertainty such as randomness and fuzziness. How do we model optimization problems in uncertain environments? How do we solve these models? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertain programming theory, including numerous modeling ideas, hybrid intelligent algorithms, and applications in system reliability design, project scheduling problem, vehicle routing problem, facility location problem, and machine scheduling problem. Researchers, practitioners and students in operations research, management science, information science, system science, and engineering will find this work a stimulating and useful reference.

Theory and practice of uncertain programming

Partnerships between companies receive a great deal of attention from top managers and researchers at the time of their formation. This attention results largely from the common perception that the initial structuring of partnerships and establishment of common goals determines partnership outcomes and success. In Alliance Advantage, Doz and Hamel shift the focus away from deal making to the internal processes within the partnership and the unfolding interactions among partners that play an important and relatively unexplored role in shaping outcomes. Focusing on the underlying reasons why companies enter alliances and the processes by which they continually learn from their interactions and re-evaluate common--and individual--goals, the authors paint a sophisticated picture of alliance dynamics over time. The authors challenge organizations to define their objectives for alliance formulation and consider whether their own corporate culture provides an "alliance ready" atmosphere.

Alliance advantage : the art of creating value through partnering

Chance constrained programming with fuzzy parameters

Uncertainty distribution is an important tool to specify an uncertain variable. In this paper, a sufficient and necessary condition of uncertainty distribution is proved to show what function is an uncertainty distribution. At the end of the paper, some special examples are given.

A sufficient and necessary condition of uncertainty distribution

A note on chance constrained programming with fuzzy coefficients

Fuzzy facility location-allocation problem under the Hurwicz criterion

This paper presents a genetic algorithm for chance constrained programming (CCP), including chance constrained goal programming(CCGP), chance constrained multiobjective programming(CCMOP). In order to deal with stochastic constraints, Monte Carlo simulation is employed to check the feasibility of a solution in the proposed genetic algorithm. Finally, we use some numerical examples to illustrate the effectiveness of genetic algorithm for chance constrained programming.

Kakuzo Iwamura

Papers

Chance constrained programming with fuzzy parameters

A sufficient and necessary condition of uncertainty distribution

A note on chance constrained programming with fuzzy coefficients

Fuzzy facility location-allocation problem under the Hurwicz criterion

A genetic algorithm for chance constrained programming