A critical review of multi-criteria decision making methods with special reference to forest management and planning

This paper provides a review of research contributions on forest management and planning using multi-criteria decision making (MCDM) based on an exhaustive literature survey. The review primarily focuses on the application aspects  highlighting theoretical underpinnings and controversies. It also examines the nature of the problems addressed and incorporation of risk into forest  management and planning decision making. The MCDM techniques covered in this review belong to several schools of thought. For each technique, a variety of empirical applications including recent studies has been reviewed. More than 60 individual studies were reviewed and classified by the method used, country of origin, number and type of criteria and options evaluated. The review serves as a guide to those interested in how to use a particular MCDM approach. Based on the review, some recent trends and future research directions are also highlighted.

Developing a fuzzy multi-criteria decision-making model for selecting design-build operational variations

Many academic researchers have conducted studies on the selection of design-build (DB) delivery method; however, there are few studies on the selection of DB operational variations, which poses challenges to many clients. The selection of DB operational variation is a multi-criteria decision making process that requires clients to objectively evaluate the performance of each DB operational variation with reference to the selection criteria. This evaluation process is often characterized by subjectivity and uncertainty. In order to resolve this deficiency, the current investigation aimed to establish a fuzzy multicriteria decision-making (FMCDM) model for selecting the most suitable DB operational variation. A three-round Delphi questionnaire survey was conducted to identify the selection criteria and their relative importance. A fuzzy set theory approach, namely the modified horizontal approach with the bisector error method, was applied to establish the fuzzy membership functions, which enables clients to perform quantitative calculations on the performance of each DB operational variation. The FMCDM was developed using the weighted mean method to aggregate the overall performance of DB operational variations with regard to the selection criteria. The proposed FMCDM model enables clients to perform quantitative calculations in a fuzzy decision-making environment and provides a useful tool to cope with different project attributes.

Application of multi-criteria decision making methods to compression ignition engine efficiency and gaseous, particulate and greenhouse gas emissions

Compression ignition (CI) engine design is subject to many constraints which presents a multi-criteria optimisation problem that the engine researcher must solve. In particular, the modern CI engine must not only be efficient, but must also deliver low gaseous, particulate and life cycle greenhouse gas emissions so that its impact on urban air quality, human health, and global warming are minimised. Consequently, this study undertakes a multi-criteria analysis which seeks to identify alternative fuels, injection technologies and combustion strategies that could potentially satisfy these CI engine design constraints. Three datasets are analysed with the Preference Ranking Organization Method for Enrichment Evaluations and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) algorithm to explore the impact of 1): an ethanol fumigation system, 2): alternative fuels (20 % biodiesel and synthetic diesel) and alternative injection technologies (mechanical direct injection and common rail injection), and 3): various biodiesel fuels made from 3 feedstocks (i.e. soy, tallow, and canola) tested at several blend percentages (20-100 %) on the resulting emissions and efficiency profile of the various test engines. The results show that moderate ethanol substitutions (~20 % by energy) at moderate load, high percentage soy blends (60-100 %), and alternative fuels (biodiesel and synthetic diesel) provide an efficiency and emissions profile that yields the most “preferred” solutions to this multi-criteria engine design problem. Further research is, however, required to reduce Reactive Oxygen Species (ROS) emissions with alternative fuels, and to deliver technologies that do not significantly reduce the median diameter of particle emissions.

Investigation of the effects of the fatty acid profile on fuel properties using a Multi-Criteria Decision Analysis

The structural features of fatty acids in biodiesel, including degree of unsaturation, percentage of saturated fatty acids and average chain length, influence important fuel properties such as cetane number, iodine value, density, kinematic viscosity, higher heating value and oxidation stability. The composition of fatty acid esters within the fuel should therefore be in the correct ratio to ensure fuel properties are within international biodiesel standards such as ASTM 6751 or EN 14214. This study scrutinises the influence of fatty acid composition and individual fatty acids on fuel properties. Fuel properties were estimated based on published equations, and measured according to standard procedure ASTM D6751 and EN 14214 to confirm the influences of the fatty acid profile. Based on fatty acid profile-derived calculations, the cetane number of the microalgal biodiesel was estimated to be 11.6, but measured 46.5, which emphasises the uncertainty of the method used for cetane number calculation. Multi-criteria decision analysis (MCDA), PROMETHEE-GAIA, was used to determine the influence of individual fatty acids on fuel properties in the GAIA plane. Polyunsaturated fatty acids increased the iodine value and had a negative influence on cetane number. Kinematic viscosity was negatively influenced by some long chain polyunsaturated fatty acids such as C20:5 and C22:6 and some of the more common saturated fatty acids C14:0 and C18:0. The positive impact of average chain length on higher heating value was also confirmed in the GAIA plane

Deconstruction plan assessment using multi-criteria decision-making methods

The purpose of this paper is to present two multi-criteria decision-making models, including an Analytic Hierarchy Process (AHP) model and an Analytic Network Process (ANP) model for the assessment of deconstruction plans and to make a comparison between the two models with an experimental case study. Deconstruction planning is under pressure to reduce operation costs, adverse environmental impacts and duration, in the meanwhile to improve productivity and safety in accordance with structure characteristics, site conditions and past experiences. To achieve these targets in deconstruction projects, there is an impending need to develop a formal procedure for contractors to select a most appropriate deconstruction plan. Because numbers of factors influence the selection of deconstruction techniques, engineers definitely need effective tools to conduct the selection process. In this regard, multi-criteria decision-making methods such as AHP have been adopted to effectively support deconstruction technique selection in previous researches. in which it has been proved that AHP method can help decision-makers to make informed decisions on deconstruction technique selection based on a sound technical framework. In this paper, the authors present the application and comparison of two decision-making models including the AHP model and the ANP model for deconstruction plan assessment. The paper concludes that both AHP and ANP are viable and capable tools for deconstruction plan assessment under the same set of evaluation criteria. However, although the ANP can measure relationship among selection criteria and their sub-criteria, which is normally ignored in the AHP, the authors also indicate that whether the ANP model can provide a more accurate result should be examined in further research.

A multi-criteria decision approach to decommissioning of offshore oil and gas infrastructure

Thousands of the world's offshore oil and gas structures are approaching obsolescence and will require decommissioning within the next decade. Many nations have blanket regulations requiring obsolete structures to be removed, yet this option is unlikely to yield optimal environmental, societal and economic outcomes in all situations. We propose that nations adopt a flexible approach that allows decommissioning options to be selected from the full range of alternatives (including 'rigs-to-reefs' options) on a case-by-case basis. We outline a method of multi-criteria decision analysis (Multi-criteria Approval, MA) for evaluating and comparing alternative decommissioning options across key selection criteria, including environmental, financial, socioeconomic, and health and safety considerations. The MA approach structures the decision problem, forces explicit consideration of trade-offs and directly involves stakeholder groups in the decision process. We identify major decommissioning options and provide a generic list of selection criteria for inclusion in the MA decision process. To deal with knowledge gaps concerning environmental impacts of decommissioning, we suggest that expert opinion feed into the MA approach until sufficient data become available. We conducted a limited trial of the MA decision approach to demonstrate its application to a complex and controversial decommissioning scenario; Platform Grace in southern California. The approach indicated, for this example, that the option 'leave in place intact' would likely provide best environmental outcomes in the event of future decommissioning. In summary, the MA approach will allow the environmental, social, and economic impacts of decommissioning decisions to be assessed simultaneously in a transparent manner. © 2013 Elsevier Ltd.

Teoria dei giochi e Multi-criteria decision-making per reti mobili Ad-hoc: un protocollo di routing

Nell'elaborato si analizzano aspetti della teoria dei giochi e della multi-criteria decision-making. La riflessione serve a proporre le basi per un nuovo modello di protocollo di routing in ambito Mobile Ad-hoc Networks. Questo prototipo mira a generare una rete che riesca a gestirsi in maniera ottimale grazie ad un'acuta tecnica di clusterizzazione. Allo stesso tempo si propone come obiettivo il risparmio energetico e la partecipazione collaborativa di tutti i componenti.

A review of multi-criteria decision-making methods for bioenergy systems

Bioenergy schemes are multi-faceted and complex by nature, with many available raw material supplies and technical options and a diverse set of stakeholders holding a raft of conflicting opinions. To develop and operate a successful scheme there are many requirements that should be considered and satisfied. This paper provides a review of those academic works attempting to deal with problems arising within the bioenergy sector using multi-criteria decision-making (MCDM) methods. These methods are particularly suitable to bioenergy given its multi-faceted nature but could be equally relevant to other energy conversion technologies. Related articles appearing in the international journals from 2000 to 2010 are gathered and analysed so that the following two questions can be answered. (i) Which methods are the most popular? (ii) Which problems attract the most attention? The review finds that optimisation methods are most popular with methods choosing between few alternatives being used in 44% of reviewed papers and methods choosing between many alternatives being used in 28%. The most popular application area was to technology selection with 27% of reviewed papers followed by policy decisions with 18%. © 2012 Elsevier Ltd.

The Use of Multi-Criteria Decision Analysis in Performing Alternatives Assessment and Comparative Risk Analysis: The Case Study of Codling Moth Pesticides

Thesis (Ph.D.)--University of Washington, 2016-08

Application of multi-criteria decision making methods to compression ignition engine efficiency and gaseous, particulate and greenhouse gas emissions

Compression ignition (CI) engine design is subject to many constraints which presents a multi-criteria optimisation problem that the engine researcher must solve. In particular, the modern CI engine must not only be efficient, but must also deliver low gaseous, particulate and life cycle greenhouse gas emissions so that its impact on urban air quality, human health, and global warming are minimised. Consequently, this study undertakes a multi-criteria analysis which seeks to identify alternative fuels, injection technologies and combustion strategies that could potentially satisfy these CI engine design constraints. Three datasets are analysed with the Preference Ranking Organization Method for Enrichment Evaluations and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) algorithm to explore the impact of 1): an ethanol fumigation system, 2): alternative fuels (20 % biodiesel and synthetic diesel) and alternative injection technologies (mechanical direct injection and common rail injection), and 3): various biodiesel fuels made from 3 feedstocks (i.e. soy, tallow, and canola) tested at several blend percentages (20-100 %) on the resulting emissions and efficiency profile of the various test engines. The results show that moderate ethanol substitutions (~20 % by energy) at moderate load, high percentage soy blends (60-100 %), and alternative fuels (biodiesel and synthetic diesel) provide an efficiency and emissions profile that yields the most “preferred” solutions to this multi-criteria engine design problem. Further research is, however, required to reduce Reactive Oxygen Species (ROS) emissions with alternative fuels, and to deliver technologies that do not significantly reduce the median diameter of particle emissions.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.

Using multi-criteria decision analysis in natural resource management

The proposed volume aims to provide useful insights on the use of Multi-criteria Decision Analysis (MCDA) in natural resource management by examining a number of empirical applications for several countries and natural resources. There is increasing interest among researchers and policy makers in using MCDA to evaluate complex management issues and problems. While several books with empirical applications have been published, these applications are very recent. Evidence from major studies suggests that MCDA approaches to the management of water, forestry, wetland and other natural resources have substantially improved the design and implementation of natural resource and environmental policies. Using innovative approaches, such as MCDA, to manage complex natural systems will enhance our understanding and management of those systems. Stakeholder involvement is an important determinant of successful resource management, and MCDA provides a useful and effective framework for getting stakeholders involved in resource management decisions. Despite the general acceptance of the role of MCDA in natural resource management, problems remain in applying these techniques. Problems include difficulties in applying the techniques, eliciting required information, lack of suitable measures for environmental variables, and development of innovative methods to simplify the use of MCDA. The proposed book examines several applications of MCDA for several countries (Australia, USA and Europe) and natural resources, including forestry, water resources and vegetation.

Modelling multi-criteria decision analysis for benchmarking management practices in project management

The link between management practices and worker’s motivations impacting construction productivity is being considered as significant among the research community. This research aimed to identify and analyse the underlying attributes impacting construction productivity from the site management perspective. This research presents a framework designed to analyse and quantify the relative relevance of different drivers in the determination of productivity levels and the degree of effectiveness of potential opportunities for improving performance of overall projects. Owing to the complexity of construction projects and underlying conflicting drivers influencing higher worker’s productivity, the Analytical Hierarchy Process (AHP) is employed to deal with interdependent relationships within a multi-criteria decision-making model. In the analytical approach, the large unstructured decision parameters are identified first and then are broken down into the manageable and measurable components using a top down hierarchical structure. This paper demonstrates an example to illustrate how to empirically analyse and prioritise a set of influencing parameters as selection criteria in devising appropriate management practices to ensure higher productivity vis-à-vis optimum performance of projects.