Multi-Criteria Analysis in Compound Decision Processes. The AHP and the Architectural Competition for the Chamber of Deputies in Rome (Italy)

In 1967, a national architectural competition was released for a preliminary project proposal, aimed at the realization of the new building for the Chamber of Deputies in Rome. The outcomes of that competition were unusual: eighteen projects were declared joint winners, and no winner was consequently selected. With reference to that event, this research aims to examine the usefulness of the evaluation tools that are currently employed and the positive effects that one of these techniques would have had, as support for the identification of the “winner” project, are highlighted. Therefore, an hypothetical examination/adjustment of the decision process of that competition through the Analytic Hierarchy Process (AHP) is developed, analyzing the outputs obtained by the implementations of this technique on the final decision. In addition to confirming the usefulness of the evaluation tools for compound and conflicting decision processes, the results of this experiment led to a further understanding of the socio-cultural dynamics related to the original outcomes of the competition analyzed. View Full-Tex

Application of Analytic Hierarchy Process to Prioritize Urban Transport Options - Comparative Analysis of Group Aggregation Methods

The present study presents a comparative analysis of different group aggregation methods adopted in AHP by testing them against social choice axioms with a case study of Delhi transport system. The group aggregation (GA) methods and their correctness were tested while prioritizing the alternative options to achieve energy efficient and less polluting transport system in Delhi It was observed that among all group aggregation methods, geometric mean method (GMM) - the most widely adopted GA method of AHP - showed poor performance and failed to satisfy the most popular pareto optimality and non-dictatorship axiom raising questions on its validity as GA method adopted in AHP. All other group aggregation methods viz. weighted arithmetic mean method with varying weights and equal weights (WAMM, WeAMM) and arithmetic mean of individual priorities (AMM) resulted in concurring results with the individual member priorities. This study demonstrates that WeAMM resulted in better aggregation of individual priorities compared to WAMM. Comparative analysis between individual and group priorities demonstrates that the arithmetic mean (AMM) of priorities by individual members of the group showed minimum deviation from the group consensus making it the most suitable and simple method to aggregate individual preferences to arrive at a group consensus.AHP, decision making, GMM, group aggregation, transportation, WAMM

Application of analytic hierarchy process to prioritize urban transport options: Comparative analysis of group aggregation methods

The present study presents a comparative analysis of different group aggregation methods adopted in AHP by testing them against social choice axioms with a case study of Delhi transport system. The group aggregation (GA) methods and their correctness were tested while prioritizing the alternative options to achieve energy efficient and less polluting transport system in Delhi. It was observed that among all group aggregation methods, geometric mean method (GMM) - the most widely adopted GA method of AHP - showed poor performance and failed to satisfy the most popular "pareto optimality and non-dictatorship axiom" raising questions on its validity as GA method adopted in AHP. All other group aggregation methods viz. weighted arithmetic mean method with varying weights and equal weights (WAMM, WeAMM) and arithmetic mean of individual priorities (AMM) resulted in concurring results with the individual member priorities. This study demonstrates that WeAMM resulted in better aggregation of individual priorities compared to WAMM. Comparative analysis between individual and group priorities demonstrates that the arithmetic mean (AMM) of priorities by individual members of the group showed minimum deviation from the group consensus making it the most suitable and simple method to aggregate individual preferences to arrive at a group consensus.AHP, decision making, GMM, group aggregation, transportation, WAMM

Predicting with sparse data

It is well known that effective prediction of project cost related factors is an important aspect of software engineering. Unfortunately, despite extensive research over more than 30 years, this remains a significant problem for many practitioners. A major obstacle is the absence of reliable and systematic historic data, yet this is a sine qua non for almost all proposed methods: statistical, machine learning or calibration of existing models. In this paper we describe our sparse data method (SDM) based upon a pairwise comparison technique and Saaty's Analytic Hierarchy Process (AHP). Our minimum data requirement is a single known point. The technique is supported by a software tool known as DataSalvage. We show, for data from two companies, how our approach — based upon expert judgement — adds value to expert judgement by producing significantly more accurate and less biased results. A sensitivity analysis shows that our approach is robust to pairwise comparison errors. We then describe the results of a small usability trial with a practising project manager. From this empirical work we conclude that the technique is promising and may help overcome some of the present barriers to effective project prediction

Formative evaluation of analytic hierarchy process as a risk prioritisation tool for risk management

The aim of this study is to discover strengths and limitations of Analytic Hierarchy Process (AHP) as a risk prioritisation tool for risk management. The study developed a risk management problem and used AHP to organise and structure risks and sub-risks of the problem. It used formative evaluation method with open-ended questionnaires to obtain feedbacks from risk managers on AHP. The study documented the following strengths of AHP: it is easy to use and understand, improves understanding of a problem and improve risk assessment. AHP improves risk assessment in the following ways: it provides a systematic risk assessment process, a clear and transparent risk assessment, facilitates debate and discussion of the risk ranking, and assists risk managers to make explicit trade-off between the risks and sub-risks. AHP is useful for problems with intangible elements, scarce data or requiring subjective judgements. AHP limitations are: too many pairwise comparisons decreasing risk managers concentration and the repetitiveness of the pairwise comparisons resulting in decision fatigue. The consequence, risk managers did not answer all questions or just answer the questions randomly

A methodology for implementing the analytical hierarchy process to decision-making in mining

A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, in fulfilment for the degree of Master of Science in Engineering Johannesburg 2015The Analytic Hierarchy Process (AHP) is a Multi Criteria Decision-Making (MCDM) tool, which has gained wide acceptance in all disciplines in science and engineering. Although it has been used in mining engineering applications, it is only recently gaining significant momentum in the mining industry. Given its simplicity, it may seem surprising that it has not received wide acceptance, but this is probably due to a lack of both publicity and a user-friendly methodology. This report introduces a simple methodology that can be employed by anyone who possesses basic knowledge of arithmetic and spreadsheets, without having to know or understand fully the mathematics that the process is based on.MT201

Coal fired power plant instrument

Coal fired is one of the most valuable sources that can be used to sustain the existence of life. Coal fired can be exploited in producing electricity. In Malaysia, there a few power plants that use coal fired as main source. To name a few, in Manjung there are coal fired plant produced 3100MW, in Tanjung Bin produced 2100MW and Jimah Power produced 1400MW. All these power plants located in South East Malaysia that used coal fired as main source. There are a lot of instrument specifically sensors and transducers applied in power plant. All these sensors and transducers used to monitor every single thing such as pressure, temperature, level and many other measurement parameters. The sensors and transducers that involved in monitoring the measurement parameters are pressure gauge, pressure transmitter, thermocouple, flow transmitter, proximity sensor, limit switch, radar, RTD and many more. Power plant applied process control system in order to link up the instruments and Human Machine Interface (HMI). HMI is a software application that presents information to an operator or user about the state of a process, and to accept and implement the operators control instructions. Typically information is displayed in a graphic format (Graphical User Interface or GUI) [1]. In general coal fired power plant or known as thermal power station is a power plant in which the prime mover steam driven. Water is heated to produce steam which drives the turbine as a result induced an electrical energy