The faculty of human cognition often finds it difficult in making decisions concerning systems that are extensive and complex such as in the management of organizational operations, investment portfolios, military command and control situations and control of nuclear facilities. Even though one may fully comprehend the individual interactions amongst a system’s variables, it is usually very difficult to predict how a system will react to new stimuli as a result of a decision taken.
Under such circumstances, the results of many researches have indicated that the judgment and decision making capabilities of human beings could well fall short of the optimal. Stress and complexities acts negatively on the human cognition system, making it even harder to make what could be termed as the most optimal decision. The decision to be taken can nevertheless be very crucial, and a wrong decision could lead to catastrophe.
It therefore becomes essential to find some way to aid and help a human being in taking crucial decisions on complex systems not only in atmospheres of stress and pressure but also in normal situations. Science has strived to device such decision-making aids through out history. Operations research, statistics and economics have developed various methods for making rational choices. The advent of Information and Communication Technology (ICT) and its dramatic developments in the last two-and-a-half decades has made it possible apply ICT in integrating various disciplines in aiding decision making in complex situations.
As a result, information science, artificial intelligence, cognitive psychology and the neurosciences have come together to develop a variety of decision making aids. These decision-making aids are practically implemented as computer applications deployed either as stand-alone tools in individual systems or are installed to cover entire working networks. Such decision-making tools and integrated computing environments are together known as Decision Support Systems (DSSs), which is a very broad term incorporating a multitude of methodologies, tools, techniques, approaches and technologies.
Druzdzel & Flynn (2002) takes all existing DSSs into consideration when they attempt to define them empirically as computer-based interactive systems that help users in making decisions. DSSs are sometimes also referred to as knowledge-based systems because they basically try to structure domain knowledge into a form on which mechanical decision making is possible. Decision Support Systems integrate information from various sources, allow intelligent access to the information sources that are relevant, and help in the process of organizing decisions to help human beings overcome their cognitive deficiencies.
Decision Support Systems strengthen the conventional tasks of accessing and retrieving information with reasoning support based on a model and model building approach. Framing, modeling and problem solving are supported by DSSs. They are usually used for strategic and tactical decisions to be made by planners and senior levels in the management. Such decisions have a reasonably low frequency but their consequences have very high potential. Therefore the time and investment taken in using DSSs to aid in taking such decisions are paid off in the long run.
Decision Support Systems not only define the alternative decision choices, but can help in picking out the most logical and optical choice amongst the alternatives adhering to and adopting elements from disciplines such as engineering economics, operations research, statistics and decision theory. Artificial Intelligence is used by Decision Support Systems to tackle problems in a heuristic manner in situations in which the problems are not amenable to formal conventional techniques.
Decision Support Systems have grown in popularity because it has been found that when decision-making systems are used appropriately they tend to increase efficiency and output providing appreciable competitive edge over rival businesses. This happens because organizations and businesses employing DSSs make sound choices in the deployment of technology, and in planning business operations, logistics and operations. Components of DSSs There are three fundamental components f Decision Support Systems are essentially made up of three basic elements: i. Data Base Management System (DBMS): The DBMS is the databank for the DSS.
The DBMS is a storehouse for the huge volumes of data that the DSS has to deal with in providing solution for the type of problem for which it has been designed. Unlike in other databases which provide physical data structure, the DMBS works on logical data structures which the users can interact with. In a good DBMS, the physical database structure and the way the data is actually process remains hidden from the user. The user only knows the different types of data that are available and how best to access this data to aid in decision making. ii. Model-Based Management System (MBMS): The MBMS plays a similar role to that of the DBMS.
The main task of an MBMS is to provide a mechanism whereby the applications that use a particular DSS are independent of the particular models that are used in the DSS. By doing so, the MBMS actually converts data available in the DBMS into information that helps in decision making. Users of a DSS usually have to handle unstructured problems. The MBMS is therefore required to help the users with building models. iii. Dialog Generation and Management system (DGMS): People use a DSS to comprehend a system in its entirety. The primary task of the DSS is therefore to provide insight.
The interfaces that a DSS uses needs to be highly user friendly as many people who use them specialize in planning and managerial decision making and may not be very well acquainted or oriented towards computing systems. The interfaces not only need to assist in building the models bit also need to provide adequate interactions with the models so that the users are able to gain insight and extract recommendations from the DSS. The DGMS is therefore primarily tasked with providing easy access and meaningful access to the DSS. DSS for Selection of Construction Materials, its relevance
This paper attempts to describe a Decision Support System to assist in making decisions to select construction materials based on a sustainability criterion. For every given construction job, there is a huge variety of construction materials to choose from. Economic factors and technology criteria have been traditionally the primary basis of selection of construction materials. Construction materials were selected against the requirements a desired life p, and a program of requirements and codes based on the characteristics of the material concerned such strength, viscosity, elasticity, bending moment, etc.
Rapid depletion of natural resources required for construction materials has however forced a change in perspectives. The focus has now shifted to ecological, health and ethical considerations. Making a selection decision based only on human judgment and past experience, taking all added aspects into consideration, becomes almost an impossible task. According to (Pearce, et. al. , 2001) it was essential that some new mechanism of assessing the available construction materials for the highest utility of the specific project was required.
The mechanism would have to evaluate the alternatives on the basis of their technical properties and cost parameters but also on the basis of the status of their availability in the ecosystem in the long-term context and from the perspective of natural resources. Such a holistic method could be implemented only through a Decision Support System. The DSS will have to provide all necessary information to enable the decision maker to take the most optimal decision keeping not only the technical and economical parameters under consideration, but also balancing the right degree of emphasis on the environment and sustainability aspect.
To achieve such an objective in the design of a Decision Support System the following development steps will have to be undertaken: 1. Sustainability will have to be defined for the selection of construction material. 2. Based on the definition of sustainability developed, a methodology has to be developed for selection and comparison of the alternative construction materials that are available. 3. The methodology for selection will have to be automated by development of a Develop a conceptual framework for a Sustainability Decision Support System (SDSS). Defining Sustainability
The United Nations World Commission on Environment and Development defines sustainable development as development keeping the concerns of the future in sight. Sustainable development is that development that meets the requirements of the present generation without in any way endangering or compromising the scope for development of future generations. (WCED, 1987). Sustainability is therefore the concept of meeting present requirements in such a manner that the resources that go to fulfill the present requirement can also be utilized to meet similar requirements in the long run.
In other words, it is handling the present with an eye on the future. This concept of sustainability works on the inherent principle that human development is a going process that has to sustained at a pace at which the finite resources available in the world can easily cope with. A fine but much simplified example could be that of utilization of timber in the making of any civil construction. The decision maker will not only have to select the timber the quality of which is suitable for the construction in terms of strength, expected durability, etc.
but will also have to ensure that the made is a type of timber that is not endangered or on the verge of being extinct, a type that is easily available in the area of the construction with no threat to its future. The next question that could face the decision maker is whether timber, considering the depletion rate of natural resources, should be used at all. And if timber is not used then what are the other available alternatives that could be used in the place of timber?
The Decision Support System will have to be able to assist the decision maker in making these crucial decisions by providing structured and easy access to all relevant information. Sustainability is therefore a system with stability at its core. Changes to the system are not unrestrained but constrained so that a stable continuance of the system is maintained in the long run. Sustainability is very important for the construction industry because constructions have a very high impact on the ecology and the environment.
The people who make decisions in the construction industry literally hold fate in their hands in the sense that considered and logical decisions based on sustainability go a long way in protecting and preserving the environment that in turn sustains human kind. Decision makers at different levels in the construction industry therefore have to make judicious selection of construction material in order fulfill the present requirements without negatively affecting the requirements of others or putting at stake the very existence of the human race on this earth.
The main goals that a DSS has to meet in selecting of construction materials based on sustainability are to improve the selection process of the construction material during the conceptual stage itself and to promote the use of innovative materials which could have more sustainable properties than the traditional materials that are currently in use. Sustainability factor in Construction Materials With regards to construction materials, adoption of sustainable selection criteria would imply the following: i. Matter and energy consumption should be minimized ii.
Minimum level of human satisfaction should be maintained. iii. There should be minimum negative environmental effects. Any effort to minimize the consumption of matter and energy has to target minimizing entropy gain and intergenerational of equity objectives. It has to be kept in mind that the process of consumption increases the entropy of materials and energy making them unsuaitable for use in the future (Roberts, 1994; Rees, 1990). The basic tenet of sustainability and sustainable material selection would therefore be maximizing utilization and minimizing consumption of matter and energy.
In laymen’s language this translates into ‘doing more with less’. Doing more with less however has to be balanced with maximizing human satisfaction with the less of matter and energy that is being consumed in the process. Unless the satisfaction of people is achieved, sustainability would run into a dead end. People and users will not accept changes necessary to make the world a better place to live in unless they are satisfied by the results of those measures. Ensuring the satisfaction of people therefore becomes an integral part of sustainability.
A part that is closely connected with economics as, in our economy-driven society, people are satisfied only when there is assurance that their economic interests will not only be safeguarded but also enhanced appreciably. Minimization of costs, maximization of comfort and safety and edification of the human spirit should be the ideal objectives in the process of selection of construction materials (Day, 1990). It all boils down to the sustainability of the human race which in turn makes it essential to ensure the sustainability and preservation of the ecosystem.
The sustainability of the ecosystem is ensured when emphasis is put on maintaining biodiversity, species habitat is left undisturbed and environmental deterioration and pollution are brought under control. The design objective of any DSS for selection of construction materials on the basis of sustainability will thus have to make these three global presumptions – less consumption of energy and matter, high human satisfaction and minimal negative effect on the environment.
A set of metrics of sustainability based on the definition of sustainability has to be developed for the construction materials. The metrics would then have to be adapted into an approach for comparing alternative materials to help in the selection process. Classification of Sustainability Attributes The next step in designing a Decision Support System for sustainable selection of construction materials would be take the attributes of sustainability and develop a system or taxonomy for classifying them into the categories of technology, ecology, economics and ethics.
Since technology is utilized to build construction facilities, it is imperative that sustainable technologies are applied. Carpenter (1994) defines sustainable technologies as technologies that do not harm the environment in any way and are based on the concept of renewing, reusing and recycling materials. Materials have to contribute to sustainability by building up suitable technologies. For a specific use, the measure of a material’s adaptability to sustainable technology is obtained by the extent to which the material is able to meet the required technical performance.
Span, reliability, ability to recycle and resistance to decay and damage are other technology-related indicators. Ecological sustainability can be achieved through material selection if the objective of material selection is to minimize environmental damage and degradation over the entire lifecycle of the material right from the stage in which the raw material is extracted to the final stage of either disposing the material or adopting it for reuse through the process of recycling.
Of particular importance in the consideration of sustainability is the way the material will affect the ecology. The domain of all human activities comprises the natural ecological systems which provide all the raw materials to meet the varied requirements of human beings (Norton 1994). Thus, integrity of the systems has to be maintained in order to ensure the continues availability of raw materials in the form of ecological resources. The search of feasible alternatives for limited natural resources leads us to the realm of economic sustainability.
Alternative resources that can be developed at minimal cost to the society have to be maintained and identified by the Decision Support System. The total life cycle cost of a project depends on the life cycle costs of the constituent construction materials. Selection of construction materials based on the lowest life cycle cost ultimately brings down the life cycle cost of the entire construction project. Manufacturing, transportation, assembly, maintenance and disposal or recycling costs determine the lifecycle cost of a construction material.
These lifecycle costs in turn determine the economic sustainability of a construction material. The moot point of sustainability is adopting a futuristic view. The concern is not only with meeting the needs of the present generation but at the same time ensuring that resource utilization is done in such a way that it is possible to retain, invest and convert them in such a way that there is no scarcity to meet the requirements of the future generations (Daly & Cobb 1994). This is the principle behind the ethics of sustainability.
The attributes of ethical sustainability are the extent of depletion of natural resources that utilization of the material could represent, extent to use the material can be reused and to which nonrenewable resources the material can be used as a substitute (Norton, 1994). The Decision Support System therefore has to base its classification of sustainability attributes on the taxonomy of technology utilized, maintenance of ecological balance, economic feasibility and ethical concerns for the future of human kind.
The vast scope and complexity of such a DSS can be appreciated when we take all these factors into consideration. Determining the Indicators of Sustainability The DSS for construction materials selection has to consider indicators of sustainability of construction materials with respect to the three global objectives of sustainable development – resource consumption, human satisfaction and environmental impact. The more exhaustive the list of indicators, the more the DSS will tend towards perfection.
Indicators could be as varied and wide ranging as the scale on which the harvesting is done, whether infrastructure for harvesting is available, how accessible the raw materials are, the extent of processing the material has to be out through, how renewable the materials, maintainability, toxicity, market pricing of comparable resources, etc. Each indicator has to be correlated with the sustainability of the material, and the correlation determined through sensitivity analysis and indexed and rated so that comparison of the materials is possible to the minutest details.
Selection of indicators of sustainability of the materials therefore assumes great importance in any DSS. Database or knowledge base development in this respect has to systematic and incremental throughout the development cycle. Consideration of the context of use also holds equal importance in the determination of sustainability of any construction material. Contextual indicators could be as apparent as the availability and use of ice blocks in the poles and sand in the deserts. But these indicators could also be user specific, condition specific or site characteristic specific.
Context modifiers therefore have to be built into any DSS. It is the context modifiers that make the sustainability ratings of construction materials for each project unique. Decision makers set threshold values in heuristics databases which enable them to specify the values that they want to be calculated. Edwards et al. (1994) and Greene (1994) give examples of techniques in transportation systems in which the energy required to transport a particular material from one place to another for various modes of transport can be calculated for different modes or types of transport. Materials Selection adopting the Rational Actor Approach
The Rational Actor Approach is centered on the principal assumption that if human decision makers are provided with complete information on the possible results and options in the choices that they have to make, they would choose the optimal alternative, or the option with the maximum possibility of turning out to be the outcome that is most wanted or desired. This being true, the goal of the DSS is to enable the decision maker to select construction materials as per their sustainability so that the vast majority of the materials selected for construction are sustainable materials.
The rational actor model has three phases (Simon, 1983): Phase 1: Determining all choices that are possible. Phase 2: Analyzing every choice for the consequences that it they may lead to. Phase 3: Finally choosing an alternative that is rated as the best based on considerations of utility and the most probable consequence or output.. In the DSS, the Rational Actor Model can be further fine tuned by the adoption of a few modifications. First, the material alternatives that are obviously not suitable for the project element could be pruned off the database based on classification of materials according to some given standards.
The software will therefore prune materials such as ceramic tiles when considering the construction of a foundation footing column. This eliminates the possibility of users ignoring feasible but unfamiliar materials. A second modification could be the introduction of user weightings for each sustainability attribute. The weightings are a way of personalizing or customizing the system. Input of the weightings accord the methodology adopted in the system higher acceptability for the user who provides the weightings. The weightings also enable customization of the sustainability of the final design product.
(Pearce, et. al. , 2001). The ordered stages of the methodology adopted with modifications can now be defined for the Decision Support System. In its first step, the methodology generates the alternatives that would be available for making the selection. This is a comprehensive set of alternatives that could include all the materials available in the market. In its second stage, the clearly infeasible alternatives are pruned from the list of available alternatives through the application of some technical performance thresholds or other heuristics.
This would result in a set of alternations that are all feasible for the application under consideration. The crucial third step consists of the Decision Support System ranking the alternatives based on the sustainability and utility of the material for the use that it is intended for. At this juncture, the decision maker feeds in his weights for each attribute of sustainability as per the priority that particular attribute holds for the decision maker.
Manufacturer information and other sources determine the values for the sustainability attributes of each material, and a normalized value is worked out for each value of the attributes. The weights and normalized values for the sustainability attributes of each material are then multiplied and added together to produce the index of subjective utility for that material. A ranking of the alternatives is developed by sorting their utility values. The Decision Support System then outputs the alternative with the highest utility value to the user.
The decision maker is at liberty to choose the highest ranked alternative for the particular application or any other alternative as he or she may deem suitable from the point of view of cognitive abilities and professional experience. The DSS then moves on to take up other design elements for consideration. From the Decision Maker’s Point of View From the decision maker’s or user’s point of view, the decision maker has to first feed in a list of the design components that have been conceptualized for the construction.
Values for relevant parameters that describe the conceptual design and the decision making have to be fed in. The DSS uses these values to generate a list of feasible materials for each design element from the materials database of the DSS utilizing heuristics for material selection from the internal logic or knowledge base of the DSS. After the DSS generates a list of feasible materials for each element, it queries the decision maker for the personalized weightings for the sustainability attributes.
The Sustainability Index Calculator calculates the values of the sustainability attributes for each feasible material. An Amalgamator Module of the DSS amalgamates the weightings of the decision maker with the sustainability attribute values for each material that could be utilized and sorts the materials according to their individual rankings. The DSS recommends the material with the highest rating to the decision maker who is free to either accept the recommendation of the Decision Support System or to opt for an alternative from the list of alternatives provided by the DSS.
Conclusions The Decision Support System for the selection of construction materials on the basis of sustainability therefore analyzes the feasible materials for each element of a construction from a wide range of perspectives. The factors that influence the ultimate output of the Decision Support System incorporate the technologies and economies of construction processes, the characteristics of the applicable materials, ecological and environmental concerns, sustainability aspects, and most important of all, the professional and personal preferences of the user or the decision maker.
Each of these factors by themselves could constitute individual expert systems. The complexity and sophistication of such decision support systems can thus be appreciated along with their great utility in helping decision makers to make crucial decisions. References -01 Carpenter, S. , 1994, Sustainable Communities. School of Public Policy, Georgia Institute of Technology, Atlanta. Daly, H. , E. , and Cobb, J. , B. , Jr. , 1994, For the Common Good, 2nd ed. Beacon Press, Boston.
Day, C. , 1990, Places of the Soul. Aquarian Press, San Francisco, CA. Druzdzel, Marek, J. , & Flynn, Roger, R. , 2002, Decision Support Systems, Decision Systems Laboratory, School of Information Sciences and Intelligent Systems Program, University of Pittsburgh, Pittsburgh. Edwards, P. ,J. , Stewart, P. ,J, Eilenberg, I. , M. , and Anton, S. , 1994, Evaluating Embodied Energy Impacts in Buildings: Some Research Outcomes and Issues, in Kibert, C. , ed. Sustainable Construction. CIB TG 16, Tampa, FL, Nov. 6-9, pp. 173-182. Greene, D. , L. , 1994, Transportation and Energy, Transportation Quarterly, v. 48, n. 1, Norton, B, G. , 1994, Sustainability: Two Competing Paradigms.
Texas A&M Conference. School of Public Policy, Georgia Institute of Technology, Atlanta. Pearce, Annie, R. , Hastak, M. , Vanegas, Jorge, A. , 2001, A Decision Support System for Construction Materials Selection using Sustainability as a Criterion, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta.
Rees, W. , E. , 1990, The Ecology of Sustainable Development, The Ecologist, v. 20, n. 1. Roberts, D. V. , 1994, Sustainable Development – A Challenge for the Engineering Profession, in Ellis, M. , D. , ed. The Role of Engineering in Sustainable Development. American Association of Engineering Societies, Washington, DC. Sage, Andrew, P. , 1991, Decision Support Systems Engineering. John Wiley & Sons, Inc. , New York. WCED – United Nations World Commission on Environment and Development. ,1987, Our Common Future. Oxford University Press, Oxford, UK.
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