نتایج جستجو برای: making mcdm

تعداد نتایج: 331655  

2014
Malcolm J. Beynon

DS/AHP is a technique for multi-criteria decision making (MCDM), based on the Dempster-Shafer Theory of evidence (DST) and the Analytic Hierarchy Process (AHP). Since its introduction it has been developed and applied by a number of authors, as well as form the foundation for other DST related MCDM techniques. This paper reviews the evolution and impact of DS/AHP, culminating in a critical pers...

2014
Lazim Abdullah Rabiatul Adawiyah

Various multi-criteria decision making (MCDM) methods have been proposed to solve diverse applications of decision problems. One of the MCDM methods is additive weighting-based method. However, this method is not explicitly disseminated and its applications are not-well received by many MCDM enthusiasts. This paper presents a review of the applications of simple additive weighting (SAW) and fuz...

Journal: :Information 2018
Rui Wang Yanlai Li

Single-valued neutrosophic hesitant fuzzy set (SVNHFS) is a combination of single-valued neutrosophic set and hesitant fuzzy set, and its aggregation tools play an important role in the multiple criteria decision-making (MCDM) process. This paper investigates the MCDM problems in which the criteria under SVNHF environment are in different priority levels. First, the generalized single-valued ne...

2015
Abdelkareem M. Alashqar Ahmad Abo Elfetouh Hazem M. El-Bakry

Evaluating software quality is an important and essential issue in the development process because it helps to deliver a competitive software product. A decision of selecting the best software based on quality attributes is a type of multi-criteria decision-making (MCDM) processes where interactions among criteria should be considered. This paper presents and develops quantitative evaluations b...

Pourhashemi, Mehdi , Zandebasiri, Mehdi ,

As the name implies, Multi Criteria Decision Making Methods (MCDMs) is a decision making tool that capable the selection of the most preferred choice in a context where several criteria apply simultaneously.  Primary purpose of this study is to examine the status of Multi Criteria Decision Making Methods (MCDMs) in forest management. The study also aims to evaluate the strengths and weaknesses ...

2005
K. SRINIVASA RAJU NAGESH KUMAR

Multicriterion decision making (MCDM) has emerged as an effective methodology due to its ability to combine quantitative and qualitative criteria for selection of the best alternative. Concurrently, fuzzy logic is gaining importance due to its flexibility in handling imprecise subjective data. In the present study two fuzzy logic-based MCDM methods, namely similarity analysis (SA) and decision ...

2013
Yong B. Shin Francis Marion

Analytic Hierarchy Process (AHP) is a powerful quantitative measurement method in the multi-criteria decision making (MCDM) area. It has been used in banks, manufacturing systems, organizational performance evaluation, and project selection. Despite this widespread usage, many studies argue that rank reversal phenomenon is unpreventable when any AHP method is applied. This paper presents that t...

2016
Xiao-hui Wu Jian-qiang Wang Juan-juan Peng Xiao-hong Chen

Simplified neutrosophic sets (SNSs) can effectively solve the uncertainty problems, especially those involving the indeterminate and inconsistent information. Considering the advantages of SNSs, a new approach for multi-criteria decision-making (MCDM) problems is developed under the simplified neutrosophic environment. First, the prioritized weighted average operator and prioritized weighted ge...

2002
SIMON MARDLE SEAN PASCOE

Management of public resources, such as fisheries, is a complex task. Society, in general, has a number of goals that it hopes to achieve from the use of public resources. These include conservation, economic, and social objectives. However, these objectives often conflict, due to the varying opinions of the many stakeholders. It would appear that the techniques available in the field of multip...

2008
Piero P. Bonissone

We consider Multi Criteria Decision Making (MCDM) as the conjunction of three components: search, preference tradeoffs, and interactive visualization. The first MCDM component is the search process over the space of possible solutions to identify the nondominated solutions that compose the Pareto set. The second component is the preference tradeoff process to select a single solution (or a smal...

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function paginate(evt) { url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term pg=parseInt(evt.target.text) var data={ "year":filter_year, "term":term, "pgn":pg } filtered_res=post_and_fetch(data,url) window.scrollTo(0,0); } function update_search_meta(search_meta) { meta_place=document.getElementById("search_meta_data") term=search_meta.term active_pgn=search_meta.pgn num_res=search_meta.num_res num_pages=search_meta.num_pages year=search_meta.year meta_place.dataset.term=term meta_place.dataset.page=active_pgn meta_place.dataset.num_res=num_res meta_place.dataset.num_pages=num_pages meta_place.dataset.year=year document.getElementById("num_result_place").innerHTML=num_res if (year !== "unfilter"){ document.getElementById("year_filter_label").style="display:inline;" document.getElementById("year_filter_place").innerHTML=year }else { document.getElementById("year_filter_label").style="display:none;" document.getElementById("year_filter_place").innerHTML="" } } function update_pagination() { search_meta_place=document.getElementById('search_meta_data') num_pages=search_meta_place.dataset.num_pages; active_pgn=parseInt(search_meta_place.dataset.page); document.getElementById("pgn-ul").innerHTML=""; pgn_html=""; for (i = 1; i <= num_pages; i++){ if (i===active_pgn){ actv="active" }else {actv=""} pgn_li="
  • " +i+ "
  • "; pgn_html+=pgn_li; } document.getElementById("pgn-ul").innerHTML=pgn_html var pgn_links = document.querySelectorAll('.mypgn'); pgn_links.forEach(function(pgn_link) { pgn_link.addEventListener('click', paginate) }) } function post_and_fetch(data,url) { showLoading() xhr = new XMLHttpRequest(); xhr.open('POST', url, true); xhr.setRequestHeader('Content-Type', 'application/json; charset=UTF-8'); xhr.onreadystatechange = function() { if (xhr.readyState === 4 && xhr.status === 200) { var resp = xhr.responseText; resp_json=JSON.parse(resp) resp_place = document.getElementById("search_result_div") resp_place.innerHTML = resp_json['results'] search_meta = resp_json['meta'] update_search_meta(search_meta) update_pagination() hideLoading() } }; xhr.send(JSON.stringify(data)); } function unfilter() { url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":"unfilter", "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } function deactivate_all_bars(){ var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(bar) { bar.dataset.active = false bar.style = "stroke:#71a3c5;" }) } year_chart.on("created", function() { var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(check) { check.addEventListener('click', checkIndex); }) }); function checkIndex(event) { var yrchart = document.querySelectorAll('.ct-bar'); var year_bar = event.target if (year_bar.dataset.active == "true") { unfilter_res = unfilter() year_bar.dataset.active = false year_bar.style = "stroke:#1d2b3699;" } else { deactivate_all_bars() year_bar.dataset.active = true year_bar.style = "stroke:#e56f6f;" filter_year = chart_data['labels'][Array.from(yrchart).indexOf(year_bar)] url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":filter_year, "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } } function showLoading() { document.getElementById("loading").style.display = "block"; setTimeout(hideLoading, 10000); // 10 seconds } function hideLoading() { document.getElementById("loading").style.display = "none"; } -->