Integrating multiple criteria decision analysis in participatory forest planning

Forest planning in a participatory context often involves multiple stakeholders with conflicting interests. A promising approach for handling these complex situations is to integrate participatory planning and multiple criteria decision analysis (MCDA). The objective of this paper is to analyze strengths and weaknesses of such an integrated approach, focusing on how the use of MCDA has influenced the participatory process. The paper outlines a model for a participatory MCDA process with five steps: stakeholder analysis, structuring of the decision problem, generation of alternatives, elicitation of preferences, and ranking of alternatives. This model was applied in a case study of a planning process for the urban forest in Lycksele, Sweden. In interviews with stakeholders, criteria for four different social groups were identified. Stakeholders also identified specific areas important to them and explained what activities the areas were used for and the forest management they wished for there. Existing forest data were combined with information from interviews to create a map in which the urban forest was divided into zones of different management classes. Three alternative strategic forest plans were produced based on the zonal map. The stakeholders stated their preferences individually by the Analytic Hierarchy Process in inquiry forms and a ranking of alternatives and consistency ratios were determined for each stakeholder. Rankings of alternatives were aggregated; first, for each social group using the arithmetic mean, and then an overall aggregated ranking was calculated from the group rankings using the weighted arithmetic mean. The participatory MCDA process in Lycksele is assessed against five social goals: incorporating public values into decisions, improving the substantive quality of decisions, resolving conflict among competing interests, building trust in institutions, and educating and informing the public. The results and assessment of the case study support the integration of participatory planning and MCDA as a viable option for handling complex forest-management situations. Key issues related to the MCDA methodology that need to be explored further were identified: 1) The handling of place-specific criteria, 2) development of alternatives, 3) the aggregation of individual preferences into a common preference, and 4) application and evaluation of the integrated approach in real case studies

Multiple-criteria decision analysis

Cilj završnog rada bio je opisati primjenu metode višekriterijske analize pri donošenju odluka. Metoda treba biti odabrana tako da se prvo usmjeri na kvalitetu i dostupnost informacija, a kao drugo treba se razumjeti kako primijeniti te informacije na sam model. Višekriterijsko donošenje odluka može se smatrati složenim i dinamičnim procesom koji uključuje menadžersku razinu odlučivanja ali isto tako mogu se primijeniti na odluke u svakodnevnom životu. Iako se odluke donose se kontinuirano i često nesvjesno, jasno je da su neke od njih su važnije od drugih. Postoje različite metode koje se mogu koristiti i često daju različite rezultate, čak i kada se primjenjuju na isti problem koristeći iste podatke. Donositelj odluke ima bitnu ulogu u samom procesu odlučivanja. Ali bez donositelja odluke ne može se primijeniti metoda odlučivanja. Metoda pomaže donosiocu odluka da donese odluku. Isto tako, može dati rješenja za povećanje kompleksnih problema upravljanja i bolje razumijevanje problema odlučivanja. Problem donošenja odluka bi trebao početi jasno definiranjem problema, razlikujući alternative, identificiranjem akcija i ciljeva u sukobu. Odabirom metode se olakšava donošenje odluke. Ne postoji loša metoda ili bolja metoda, treba samo pronaći metodu koja se razumije te će onda postati laka za korištenje i koja će odgovarati određenoj situaciji. PROMEETHE metoda koja je uzeta kao primjer. Koristi se širom svijeta u mnogim različitim područjima. Metoda PROMETHEE I koristi se da se dobije djelomično rangiranje svih mogućih razmatranih alternativa, dok PROMETHEE II se koristi za dobivanje kompletnog ranga. Metoda se primjenjuje jer dozvoljava izravno korištenje podataka za odabrani problem. Donositelj odluke sam određuje kriterije te na osnovi rezultata dobiva analitičko i grafičko rješenje. U radu su korištena dva softvera koja su lagana za korištenje: SmartPicker Pro i D-Sight

Multiple-criteria decision analysis

Cilj završnog rada bio je opisati primjenu metode višekriterijske analize pri donošenju odluka. Metoda treba biti odabrana tako da se prvo usmjeri na kvalitetu i dostupnost informacija, a kao drugo treba se razumjeti kako primijeniti te informacije na sam model. Višekriterijsko donošenje odluka može se smatrati složenim i dinamičnim procesom koji uključuje menadžersku razinu odlučivanja ali isto tako mogu se primijeniti na odluke u svakodnevnom životu. Iako se odluke donose se kontinuirano i često nesvjesno, jasno je da su neke od njih su važnije od drugih. Postoje različite metode koje se mogu koristiti i često daju različite rezultate, čak i kada se primjenjuju na isti problem koristeći iste podatke. Donositelj odluke ima bitnu ulogu u samom procesu odlučivanja. Ali bez donositelja odluke ne može se primijeniti metoda odlučivanja. Metoda pomaže donosiocu odluka da donese odluku. Isto tako, može dati rješenja za povećanje kompleksnih problema upravljanja i bolje razumijevanje problema odlučivanja. Problem donošenja odluka bi trebao početi jasno definiranjem problema, razlikujući alternative, identificiranjem akcija i ciljeva u sukobu. Odabirom metode se olakšava donošenje odluke. Ne postoji loša metoda ili bolja metoda, treba samo pronaći metodu koja se razumije te će onda postati laka za korištenje i koja će odgovarati određenoj situaciji. PROMEETHE metoda koja je uzeta kao primjer. Koristi se širom svijeta u mnogim različitim područjima. Metoda PROMETHEE I koristi se da se dobije djelomično rangiranje svih mogućih razmatranih alternativa, dok PROMETHEE II se koristi za dobivanje kompletnog ranga. Metoda se primjenjuje jer dozvoljava izravno korištenje podataka za odabrani problem. Donositelj odluke sam određuje kriterije te na osnovi rezultata dobiva analitičko i grafičko rješenje. U radu su korištena dva softvera koja su lagana za korištenje: SmartPicker Pro i D-Sight

Including cognitive aspects in multiple criteria decision analysis

"First Online: 21 December 2016"Many Multiple Criteria Decision Analysis (MCDA) methods have been proposed over the last decades. Some of the most known methods share some similarities in the way they are used and configured. However, we live in a time of change and nowadays the decision-making process (especially when done in group) is even more demanding and dynamic. In this work, we propose a Multiple Criteria Decision Analysis method that includes cognitive aspects (Cognitive Analytic Process). By taking advantage of aspects such as expertise level, credibility and behaviour style of the decision-makers, we propose a method that relates these aspects with problem configurations (alternatives and criteria preferences) done by each decision-maker. In this work, we evaluated the Cognitive Analytic Process (CAP) in terms of configuration costs and the capability to enhance the quality of the decision. We have used the satisfaction level as a metric to compare our method with other known MCDA methods in literature (Utility function, AHP and TOPSIS). Our method proved to be capable to achieve higher satisfaction levels compared to other MCDA methods, especially when the decision suggested by CAP is different from the one proposed by those methods.This work was supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the João Carneiro PhD grant with the reference SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersio

Participatory forest planning and multiple criteria decision analysis (MCDA)

With the industrial revolution, the human utilization of the forest took a new turn as wood became a commercial product (Östlund & Zackrisson 2000). Since then, economical considerations have pervaded the public perspective on forest and forestry. However, the awareness of the need for sustainability in the use of the forest resource has also grown, and during the last decades other values have entered the discussion and the practice of forestry. Today, sustainable forest management (SFM) where economical, ecological and social values are all satisfied, is a core element in the development of acceptable forest management practices. Public participation is strongly related to SFM. In some industrialized countries, e.g. Canada, demands for participation in natural resource management have subsequently been incorporated into the legislation (Chambers and Beckley 2003), but in most countries there is no legal demand for participation. In Sweden for example, the only demand for participation in the Forestry Act is consultation before clear cutting in certain areas of reindeer herding. Forest certification, which is now covering extensive areas in several countries, plays an interesting role in the promotion of SFM. However, its main purpose is not public participation and the integration of social values into forestry (Angelstam et al. 2004). Internationally, there is the Aarhus Convention on Access to Information, Public Participation in Decision Making and Access to Justice in Environmental Matters. This convention has been ratified by Sweden amongst other countries, but it is difficult to make a strict interpretation of it. New approaches and methods are obviously needed in forest management planning to incorporate forest values other than timber production and to help solve conflicts of interest. There have been some attempts made by different types of projects. The Canadian Model Forest concept promotes participation in the work for SFM, and has been tried out in Sweden in the Vilhelmina Model Forest project (Svensson et al. 2004). Some of the LIFE projects sponsored by the European Union are also applications of participation with SFM as the objective; the project “Local Participation in Sustainable Forest Management based on Landscape Analysis” is a Swedish example of a LIFE project sponsored by the European Union (http://www.svo.se/minskog/templates/svo_se_vanlig.asp?id=8001, 2007-01-12). A potentially powerful tool in the work for sustainable forest management (SFM) and participation is multiple criteria decision analysis (MCDA), an approach which can make it possible to handle complex decision situations involving conflicting interests and several stakeholders. The purpose of this paper is to clarify concepts related to participation and present methods that are applicable in participatory planning. More specifically the following questions will be dealt with: • What is meant by participation? What methods and techniques are available to participatory planning processes? • What is MCDA and what phases do this approach require? In order to illuminate the state of art of participatory planning in forestry, an analysis of a number of case studies is presented

An OWA-TOPSIS method for multiple criteria decision analysis

A hybrid approach integrating OWA (Ordered Weighted Averaging) aggregation into TOPSIS (technique for order performance by similarity to ideal solution) is proposed to tackle multiple criteria decision analysis (MCDA) problems. First, the setting of extreme points (ideal and anti-ideal points) in TOPSIS is redefined and extended for handling the multiple extreme points situation where a decision maker (DM) or multiple DMs can provide more than one pair of extreme points. Next, three different aggregation schemes are designed to integrate OWA into the TOPSIS analysis procedure. A numerical example is provided to demonstrate the proposed approach and the results are compared for different aggregation settings and confirm the robustness of rankings from different scenarios

Multiple criteria decision analysis with consideration to place-specific values in participatory forest planning

The combination of multiple criteria decision analysis (MCDA) and participatory planning is an approach that has been applied in complex planning situations where multiple criteria of very different natures are considered, and several stakeholders or social groups are involved. The spatial character of forest planning problems adds further to the complexity, because a large number of forest stands are to be assigned different treatments at different points in time. In addition, experience from participatory forest planning indicates that stakeholders may think about the forest in terms of place-specific values rather than in forest-wide terms. The objective of this study was to present an approach for including place-specific values in MCDA-based participatory forest planning and illustrate the approach by a case study where the objective was to choose a multipurpose forest plan for an area of urban forest in northern Sweden. Stakeholder values were identified in interviews, and maps were used to capture place-specific spatial values. The nonspatial and nonplace-specific spatial values were formulated as criteria and used to build an objective hierarchy describing the decision situation. The place-specific spatial values were included in the creation of a map showing zones of different silvicultural management classes, which was used as the basis for creation of forest plan alternatives in the subsequent process. The approach seemed to work well for capturing place-specific values, and the study indicates that formalized methods for including and evaluating place-specific values in participatory forest planning processes should be developed and tested further

Flood Emergency Response System Using Multiple Criteria Decision Analysis

Recently, several states in Malaysia have been affected by flood disasters, causing hundred thousands of people to be evacuated from their homes and some of the victims killed on the floods. Therefore, flood emergency response at early stage is very important to keep flood risk and its impact at the very minimum level. However, it is not easy to come up with the best flood emergency response plan. The reason is because flood management problems related to the emergency response are inherently complex, time-bound, involving with conflicting priorities and in need of high decision stakes. So, application of Multi-Criteria Decision Analysis (MCDA) is being studied and is used in this project. It can help search and rescue teams to manage those complexity and decisions load by combining value judgments and technical information in a structured MCDA decision framework. This report will discuss the currently research done on the project called Flood Emergency Response System. With a promising results after a few test, it shows that this system is a proven tools that help search and rescue teams to locate and save the flood victims efficiently based on their prioritization of their condition. The objectives of the flood emergency response system is to provide a platform for the rescuers to locate and prioritize which flood victims that they should save first. This system can provide an auto-generated ranking of the current flood victims available in the system for the rescuer to view which place that they should go first in order to save the victims. A brief overview of the system is presented and future research directions of this project are further discussed in this report. In summary, by making the links among flood knowledge, assumptions and choices more explicit by using the application of MCDA, the system is able to increase decision-making effectiveness, efficiency and transparency, which consequently can help the search and rescue teams to saves more lives and reduces flood management costs during the occurrence of flood disaste

A speedy cardiovascular diseases classifier using multiple criteria decision analysis

Each year, some 30 percent of global deaths are caused by cardiovascular diseases. This figure is worsening due to both the increasing elderly population and severe shortages of medical personnel. The development of a cardiovascular diseases classifier (CDC) for auto-diagnosis will help address solve the problem. Former CDCs did not achieve quick evaluation of cardiovascular diseases. In this letter, a new CDC to achieve speedy detection is investigated. This investigation incorporates the analytic hierarchy process (AHP)-based multiple criteria decision analysis (MCDA) to develop feature vectors using a Support Vector Machine. The MCDA facilitates the efficient assignment of appropriate weightings to potential patients, thus scaling down the number of features. Since the new CDC will only adopt the most meaningful features for discrimination between healthy persons versus cardiovascular disease patients, a speedy detection of cardiovascular diseases has been successfully implemented