http://web.aeromech.usyd.edu.au/AMME4500/mpc_survey.pdf

A survey of industrial model predictive control technology

A prevalent and pervasive view of designing is that it can be modeled using variables and decisions made about what values should be taken by these variables. The activity of designing is carried out with the expectation that the designed artifact will operate in the natural world and the social world. These worlds impose constraints on the variables and their values; so, design could be described as a goal-oriented, constrained, decision- making activity. However, design distinguish- es itself from other similarly described activities not only by its domain but also by additional necessary features. Designing involves exploration, exploring what variables might be appropriate. The process of explo- ration involves both goal variables and deci- sion variables. In addition, designing involves learning: Part of the exploration activity is learning about emerging features as a design proceeds. Finally, design activity occurs within two contexts: the context within which the designer operates and the context produced by the developing design itself. The designer’s perception of what the context is affects the implication of the context on the design. The context shifts as the designer’s perceptions change. Design activity can be now characterized as a goal-oriented, con- strained, decision-making, exploration, and learning activity that operates within a con- text that depends on the designer’s percep- tion of the context.

Design Prototypes: A Knowledge Representation Schema for Design

http://www.roodbergen.com/publications/EJOR2009.pdf

A survey of literature on automated storage and retrieval systems

Simultaneous approaches for dynamic optimization problems are surveyed and a number of emerging topics are explored. Also known as direct transcription, this approach has a number of advantages over competing dynamic optimization methods. Moreover, a number of industrial applications have recently been reported on challenging real-world applications. This study provides background information, summarizes the underlying concepts and properties of this approach, discusses recent advances in the treatment of discrete decisions and, finally, illustrates the approach with two process case studies.

An overview of simultaneous strategies for dynamic optimization

The fuzzy VIKOR method has been developed to solve fuzzy multicriteria problem with conflicting and noncommensurable (different units) criteria. This method solves problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to handle imprecise numerical quantities. Fuzzy VIKOR is based on the aggregating fuzzy merit that represents distance of an alternative to the ideal solution. The fuzzy operations and procedures for ranking fuzzy numbers are used in developing the fuzzy VIKOR algorithm. VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria, and on proposing compromise solution (one or more). It is extended with a trade-offs analysis. A numerical example illustrates an application to water resources planning, utilizing the presented methodology to study the development of a reservoir system for the storage of surface flows of the Mlava River and its tributaries for regional water supply. A comparative analysis of results by fuzzy VIKOR and few different approaches is presented.

http://www.irantahgig.ir/wp-content/uploads/40090.pdf

Fuzzy VIKOR with an application to water resources planning

A parametric representation of fuzzy numbers and their arithmetic operators

Analysis of the error in the standard approximation used for multiplication of triangular and trapezoidal fuzzy numbers and the development of a new approximation

This paper studies a new class of optimization problems which have multiple objective functions subject to a set of fuzzy relation equations. Since the feasible domain of such a problem is in general non-convex and the objective functions are not necessarily linear, traditional optimization methods may become ineffective and inefficient. Taking advantage of the special structure of the solution set, a reduction procedure is developed to simplify a given problem. Moreover, a genetic-based algorithm is proposed to find the "Pareto optimal solutions". The major components of the proposed algorithm together with some encouraging test results are reported.

Multi-objective optimization problems with fuzzy relation equation constraints

This paper presents a new approach to concurrent engineering, namely the use of artificial intelligence constraint networks to advise the designer on improvements that can be made to the design from the perspective of the product's life-cycle. The difficulties associated with performing concurrent engineering are reviewed, and the various approaches to concurrent engineering are discussed. The requirements for a system to support concurrent engineering are indicated. An overview of constraint networks is given and this leads into a description of SPARK, an artificial intelligence constraint network systems for concurrent engineering. The operation of SPARK is illustrated by considering an example application of printed wiring board manufacture. The advantages of SPARK include being flexible enough to allow the designer to approach a problem from a variety of viewpoints, allowing the designer to design despite having incomplete information, and being able to handle the wide variety of life-cycle informatio...

Robert E. Young

Papers

A parametric representation of fuzzy numbers and their arithmetic operators

Analysis of the error in the standard approximation used for multiplication of triangular and trapezoidal fuzzy numbers and the development of a new approximation

Multi-objective optimization problems with fuzzy relation equation constraints

An artificial intelligence-based constraint network system for concurrent engineering

Configuring computer systems through constraint-based modeling and interactive constraint satisfaction