to provide an international clearing house for computational (as well as related theoretical) aspects of optimization problems in diverse areas and to share computing experience gained on specific applications;
to promote the development of necessary high-level theory to meet the needs of complex optimization problems and establish appropriate cooperation with the International Mathematics Union and similar organisations;
to foster interdisciplinary activity on optimization problems spanning the various areas such as Economics (including Business Administration and Management), Biomedicine, Meteorology, etc., in cooperation with associated international bodies.
Computational aspects of optimization problems arising in such areas as Aerospace, Biomedicine, Economics, Meteorology, and Public Services (Health, Environment, Police, Fire, Transportation, etc.).
Some specific examples are:
on-line and off-line computational techniques in modelling and control of dynamic systems;
trajectory analysis and computation;
optimization of decentralized systems (macro-economic systems) and systems with multicriteria;
optimization of resource allocation in urban systems;
optimization of pollution-control systems;
optimization of man-machine systems;
optimization of power systems operation.
WG7.1 - Modeling and Simulation
To foster cooperation and information interchange among those engaged in the simulation of large and complex systems including specialists in:
Modelling and Identification Methodology;
Computer Simulation Languages;
Interactive On-Line Computation;
The work will include three major classes of problems:
using various approaches such as:
new simulation languages for digital simulation;
new computer graphics techniques;
application of pattern recognition and feature extraction methods;
new mathematical techniques (e.g. finite elements);
new data base organisations and simulations of data bases.
To foster the international exchange of ideas and experience in the area of Computational Techniques with particular emphasis on distributed systems arising in diverse disciplines such as Mechanics, Economics, Biomedical Engineering, Geophysics, etc.
Computational Techniques for Identification and Optimal Control of Systems Modelled by Partial Differential Equations;
Computational Techniques for Structural Problems, Elasticity, Plasticity, etc., including various approaches such as: Finite Element Approximation Techniques, Decomposition Techniques, Interactive and Graphic Computer Techniques.
WG7.3 - Computer Systems Modeling
The work of the Group is directed toward improving the art of analyzing and optimizing performance and costs of data processing systems through the use of analytical models.
optimized allocation of resources (such as memory, telecommunication lines, computer power, and points of concentration and switching), in distributed information processing systems;
analyses of throughput and response time;
analyses of reliability in the presence of failures of hardware, software or telecommunications;
analyses of CPU main memory and I/O channel scheduling and allocating procedures;
analyses of storage systems including memory hierarchies and geographically distributed data bases;
comparison with simulations and with performance indices measured experimentally.
WG7.4 - Inverse Problems and Imaging
To foster cooperation between experts in the fields of inverse problems and imaging on the development of reliable and efficient reconstruction methodologies and the convergence analysis of algorithms. To also stimulate exchange with other working groups in TC7, e.g., on optimization and control methods, modelling with differential equations, and stochastic aspects.
A core topic of common interest of this working group is variational methods for solving inverse and imaging problems. The members of the working group additionally contribute to the technical committee their specific expertise on aspects related to these areas of, e.g., mathematical modelling, optimization techniques, partial differential equations, harmonic analysis, regularization techniques, parameter identification, recovery of interfaces, and stochastic noise modelling.
AIMS and SCOPES
Promote modern structural system reliability and optimization theory;
Advance international cooperation in the field of structural system reliability and optimization theory;
Stimulate research, development and application of structural system reliability and optimization theory;
Disseminate and exchange the information on reliability and optimization of structural systems;
Encourage education in structural system reliability and optimization theory.
WG7.6 - Optimization-Based Computer Aided
Modeling and Design
est. 1989, revised 1999
The Working Group 7.6 considers high-performance computer-aided systems to support modelling, decision analysis, optimization and multi-criteria decision making.
The Working Group is focused on
Policy and Management (Application Focus)
Optimization, Multi-Criteria Decision Analysis and Simulation (Methodological Focus)
Design, Planning and Scheduling (Problem Type Focus)
Modelling and Implementation of Intelligent Systems (Information Technology Focus)
Any methodological approach or combination of solution techniques, which solves real world problems successfully. Thus, the following problem types are examples of application areas in policy and management the WG will deal with:
Network Design (Communication, Transportation, Traffic)
Planning and Scheduling in Transportation Logistics
Production Planning and Scheduling
Environmental. Planning Problems
WG7.7 - Stochastic Optimization
To foster international cooperation among experts in stochastic optimization, and to spread information about the achievements of the field into areas of possible applications.
Subject of this WG are all problems involving in an essential way stochastic components (variables or processes) and the task of optimizing functions. In particular this includes:
Theoretical investigation of stochastic optimization models;
Design, development and analysis of solution methods;
Modelling practical problems by stochastic optimization problems, e.g. in agriculture, industrial production, finance, power systems, water reservoir management, and implementing stochastic optimization models into decision support systems.