C. Henggeler Antunes

A Multiple Objective Linear Programming Approach to Power Generation Planning with Demand‐Side Management (DSM)

The optimization of an economic indicator has traditionally been the sole objective function of mathematical programming models for power generation expansion planning. Recently, however, other evaluation aspects, such as environmental concerns, were also given an explicit role as objective functions in mathematical models. Models become thus more realistic so that decision makers are able to grasp the inherent conflicts and trade-offs among the distinct objectives in selecting a best compromise plan. A significant change in the planning processes has also occurred concerning new planning methodologies integrating demand-side management (DSM) techniques, in an attempt to change the levels and forms of electricity use by the consumers. This paper presents a multiple objective linear programming model for power generation expansion planning incorporating DSM. The objective functions are the total expansion cost, the environmental impact associated with the installed power capacity and the environmental impact associated with the energy output. DSM is included by modelling it as a new generating group along with the generating alternatives from the supply side. Five categories of constraints are considered related to the reliability of the supply system, the availability of the generating units, the capacity of the DSM-equivalent generating group, the total capacity installed throughout the planning period, the pollutant emissions. Some results are presented derived by using an interactive method, aimed at assisting decision makers in a progressive and selective search of good compromise solutions.

Interactive decision support for multiobjective transportation problems

Abstract This paper presents a linear programming solution methods called TRIMAP, that is dedicated to solving three-objective transportation problems. A new version of the package, developed for this purpose, integrates an efficient basic primal simplex algorithm specialized to solve pure minimum cost flow problems and new interfaces for displaying each solution in graphical network form. The interactive capabilities of TRIMAP seem to be very useful for exploiting this type of problem, namely by enabling in an interactive way a progressive and selective identification of the set of nondominated solutions.

An integrated MOLP method base package: a guided tour of TOMMIX

Abstract An implementation of a MOLP interactive method base is presented in the form of a guided tour to a computer package. The MOLP method base (associated to a procedure toolbox) is a component of a decision support system framework which also integrates a dialogue base and a data management module. Besides providing the standard working of each method the interactive MOLP method base offers the possibility of method switching at any interaction with the decision maker (DM), in order to make the most of the potentialities of each method and support a “learning” process. Some key issues in the development of interactive MOLP approaches and computational tools are also discussed. Special attention is paid to the development of an user-friendly environment for interacting with the DM.

Design of an adaptive mutation operator in an electrical load management case study

An adequately designed and parameterized set of operators is crucial for an efficient behaviour of Genetic Algorithms (GAs). Several strategies have been adopted in order to better adapt parameters to the problem under resolution and to increase the algorithms performance. One of these approaches consists in using operators presenting a dynamic behaviour, that is displaying a different qualitative behaviour in different stages of the evolutionary process. In this work a comparative analysis of the effects of using an adaptive mutation operator is presented in the operational framework of a multi-objective GA for the design and selection of electrical load management strategies. It is shown that the use of a time/space varying mutation operator depending on the values achieved for each objective function increases the performance of the algorithm.

A decision support system dedicated to discrete multiple criteria problems

Abstract In most real world contexts, decisions must be made in presence of multiple, conflicting, incommensurate criteria. This paper presents a computational tool aimed at providing decision aid in the evaluation of a finite and explicitly known set of alternatives over several criteria. The system has been designed as an experimentation framework for helping analysts in the practice of decision aid, and it can be customized to specific decision situations. This decision support system (DSS) consists of a problem editor, a problem compiler, a set of multiple criteria decision aid (MCDA) methods, a dialogue base and a data management module. The DSS intends to make the most of a user-friendly computer interface in order to minimize the cognitive effort required from decision makers (DMs). The set of methods includes some representative discrete alternative MCDA methods, underlying different philosophies and strategies for selecting, clustering or ranking the alternatives. Some features of this DSS will be illustrated by considering a case study of evaluation of alternative power generation expansion policies.

On the integration of an interactive MOLP procedure base and expert system techniques

Abstract This paper presents a computer implementation of a multiple objective linear programming procedure base which is integrated with Expert System techniques in order to provide decision aiding to decision makers. In the context of an energy planning case study it is discussed how the integration of the procedural component with Expert System techniques can improve the decision makers perception of the problem and guide the interactive search process, by using different levels of knowledge. The aim is to aid the decision maker in processing the information having in mind not just explore the problem but also his/her preference structure in order to obtain satisfactory solutions.

From TRIMAP to SOMMIX — Building Effective Interactive MOLP Computational Tools

This paper aims at presenting a path of development of interactive computational tools devoted to provide decision aid in multiple objective linear programming (MOLP) problems, made by a research team at the University of Coimbra. After referring to the motivation of this research area, the main characteristics of the research work which has been carried out in the last years are described, with special emphasis on the MOLP interactive environments TRIMAP, TOMMK and SOMMIX.

Multi-Objective Evolutionary Approaches for Reactive Power Planning in Electrical Networks - an Overview

Since the 1960s a great deal of attention has been paid to the problem of reactive power compensation in electrical networks. This problem consists in providing the appropriate location and sizing of compensation devices, aimed at ensuring satisfactory voltage profile and reduce power losses, while minimizing the compensation cost. In recent years the methodologies to solve this problem shifted from mathematical programming algorithms to metaheuristics and, in particular, to Evolutionary Algorithms (EAs). EAs can provide good quality solutions without requiring mathematical model simplifications. Moreover, EAs are well suited to multi-objective problems because they work with a population of solutions. This paper makes an overview of the application of multi-objective EAs to the reactive power planning problem.

State of the Art on Retrofit Strategies Selection Using Multi-objective Optimization and Genetic Algorithms

The retrofit of a building involves not just the fulfillment of functional requirements, but also considerations such as investment costs, energy consumption, environmental impact, and occupant well-being. Careful long-term decisions in the retrofit and operation of buildings can significantly improve their thermal performance and thus reduce their consumption of energy. Moreover, they can improve indoor environmental quality in buildings. Alternative building energy conservation measures, standards compliance, and economic optimization can be evaluated using available energy analysis and decision-aid techniques. These may range from simplified energy analysis methods for approximate energy use estimates to detailed computerized hourly simulation coupled with decision-aid techniques. This chapter reviews the research and development in the decision support processes in building retrofit. Special attention is devoted to the methodologies using multi-objective optimization and genetic algorithms. Accordingly, the decision methodologies are broadly separated into two main categories: approaches in which alternatives are explicitly known a priori and approaches in which alternatives are implicitly defined by an optimization model. The advantages and drawbacks of the various methods in each category are also discussed.

Decision Aiding in an Organizational Context

The increasing complexity of the social and economical environment, as well as the rapid pace of development in computer and communication sciences and technologies, have created situations which require not only the modernization of the organizations but also new types of planning and management. Under these changing conditions new forms of decision support must be developed, giving decision makers an active role throughout the decision making process. Decision support systems provide a technological support for learning in an organizational context. Our approach will be illustrated by means of operational decision support systems dedicated to rural telephone network planning and multicriteria problems.