scholarly journals Optimising Rig Design for Sailing Yachts with Evolutionary Multi-Objective Algorithm

2020 ◽  
Vol 27 (4) ◽  
pp. 36-49
Author(s):  
Mikołaj Pawłusik ◽  
Rafał Szłapczyński ◽  
Artur Karczewski
Keyword(s):  
Decision Making ◽  
Evolutionary Algorithms ◽  
Pareto Set ◽  
Dominance Relation ◽  
Multi Criteria Decision Making ◽  
Control Parameters ◽  
Multi Objective ◽  
Sailing Yacht

AbstractThe paper presents a framework for optimising a sailing yacht rig using Multi-objective Evolutionary Algorithms and for filtering obtained solutions by means of a Multi-criteria Decision Making method. A Bermuda sloop with discontinuous rig is taken under consideration as a model rig configuration. It has been decomposed into its elements and described by a set of control parameters to form a responsive model which can be used for optimisation purposes. Considering the contradictory nature of real optimisation objectives, a multi-objective approach has been chosen to address this issue. Once the optimisation process is over, a Multi-criteria Decision Making method based on a w-dominance relation is applied for filtering out the most interesting solutions from the obtained Pareto set. The proposed method has been implemented, and selected results are provided and discussed.

A review of multi-objective optimisation and decision making using evolutionary algorithms

2019 ◽  
Vol 14 (2) ◽  
pp. 69 ◽  
Author(s):  
Muneendra Ojha ◽  
Krishna Pratap Singh ◽  
Pavan Chakraborty ◽  
Shekhar Verma
Keyword(s):  
Decision Making ◽  
Evolutionary Algorithms ◽  
Multi Objective

Multi-objective mathematical model based on fuzzy hybrid multi-criteria decision-making and FMEA approach for the risks of oil and gas projects

2020 ◽  
Vol 18 (6) ◽  
pp. 1997-2016
Author(s):  
Mohammad Khalilzadeh ◽  
Rose Balafshan ◽  
Ashkan Hafezalkotob
Keyword(s):  
Decision Making ◽  
Oil And Gas ◽  
Programming Model ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Multi Objective ◽  
Response Strategies ◽  
Fuzzy Environment ◽  
Comprehensive Framework ◽  
Grey Relational

Purpose The purpose of this study is to provide a comprehensive framework for analyzing risk factors in oil and gas projects. Design/methodology/approach This paper consists of several sections. In the first section, 19 common potential risks in the projects of Pars Oil and Gas Company were finalized in six groups using the Lawshe validation method. These factors were identified through previous literature review and interviews with experts. Then, using the “best-worst multi-criteria decision-making” method, the study measured the weights associated with the performance evaluation indicators of each risk. Consequently, failure mode and effects analysis (FMEA) and the grey relational analysis (GRA)-VIKOR mixed method were used to rank and determine the critical risks. Finally, to assign response strategies to each critical risk, a zero-one multi-objective mathematical programming model was proposed and developed Epsilon-constraint method was used to solve it. Findings Given the typical constraints of projects which are time, cost and quality, of the projects that companies are often faced with, this study presents the identified risks of oil and gas projects to the managers of the oil and gas company in accordance with the priority given in the present research and the response to each risk is also suggested to be used by managers based on their organizational circumstances. Originality/value This study aims at qualitative management of cost risks of oil and gas projects (case study of Pars Oil and Gas Company) by combining FMEA, best worst and GRA-VIKOR methods under fuzzy environment and Epsilon constraints. According to studies carried out in previous studies, the simultaneous management of quantitative and qualitative cost of risk of oil and gas projects in Iran has not been carried out and the combination of these methods has also been innovated.

Progressive Multi-Objective Optimization

2014 ◽  
Vol 13 (05) ◽  
pp. 917-936 ◽  
Author(s):  
Kenneth Sörensen ◽  
Johan Springael
Keyword(s):  
Decision Making ◽  
Knapsack Problem ◽  
Multi Criteria Decision Making ◽  
Multi Objective Optimization ◽  
Sequential Approach ◽  
Nondominated Solutions ◽  
Multi Objective ◽  
Novel Technique ◽  
Single Solution ◽  
Set Approximation

This paper introduces progressive multi-objective optimization (PMOO), a novel technique to include the decision maker's preferences into the multi-objective optimization process. PMOO integrates a well-known method for multi-criteria decision making (PROMETHEE) into a simple multi-objective metaheuristic by maintaining and updating a small reference archive of nondominated solutions throughout the search. By applying this novel technique to a set of instances of the multi-objective knapsack problem, the superiority of PMOO over the commonly accepted sequential approach of generating a Pareto set approximation first and selecting a single solution afterwards is demonstrated.

scholarly journals إستعمال إسلوب تعدد الأهداف الأمثل وفقاً للتحليل النسبي مع تطبيق عملي

2020 ◽  
Vol 26 (122) ◽  
pp. 412-421
Author(s):  
Mohamed Naji Razooqee ◽  
Marwan Abdul Hameed Ashour
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Composite Score ◽  
Multi Criteria Decision Making ◽  
Multi Objective Optimization ◽  
Analytic Hierarchy ◽  
Multi Objective ◽  
Hierarchy Process

يهدف البحث الى حل مشكلة إختيار المشروع المناسب من عدة مشاريع خدمية لمؤسسة الشهداء العراقية أو ترتيبها حسب الافضلية ضمن المعايير المستهدفة من قبل متخذ القرار، يتم  ذلك عن طريق إستعمال احدى الطرق الكمية في اتخاد القرارات متعددة الأهداف (Multi Criteria Decision  Making)  ((MCDM الا وهي طريقة التحسين متعدد الأهداف حسب التحليل النسبي (Multi Objective Optimization by Ratios Analysis) ((MOORA لقياس الدرجة المركبة (composite score) للأداء  الذي يحصل عليه كل بديل وأقصى فائدة تعود على الجهة المستفيدة وحسب المعايير واوزانها التي يتم حسابها عن طريق عملية التسلسل الهرمي التحليلي (Analytic Hierarchy Process) ((AHP ، اهم النتائج التي توصل اليها البحث وبالأعتماد على رأي الخبراء هي إختيار المشروع الثاني كأفضل بديل وعمل ترتيب (Ranking) حسب الأداء والدرجة المركبة التي حصل عليها كل بديل ، كما توصل الباحثون الى امكانية تطبيق النموذج لحل مختلف مشاكل (MCDM) وخاصة في الحالات التي تكون فيها المعايير متضاربة في مزيد من البحوث.

scholarly journals FMADM: YAGER MODEL IN FUZZY DECISION MAKING

2018 ◽  
Vol 12 (1) ◽  
pp. 1
Author(s):  
Kisworo Kisworo
Keyword(s):  
Decision Making ◽  
Standard Form ◽  
Team Work ◽  
Fuzzy Decision Making ◽  
Multi Criteria Decision Making ◽  
Fuzzy Decision ◽  
Multi Objective ◽  
Decisionmaking Process ◽  
Decision Environment

This paper presents Yager model, i.e. standard form of Fuzzy Multi-Atributte Decision Making (FMADM) in fuzzy decision environment. Simulasion of this model would be performed under scope of fuzzy decisionmaking process to show its existence. As academics, researchers, and practitioners know on it, besides theFMADM, so is there Fuzzy Multi-Objective Decision Making (FMODM) at where the both has their same derivation, e.i. Fuzzy Multi-Criteria Decision Making (FMCDM). Related to the matter, significant value that could be represented then gives contribution to team work-oriented principal of decision makers.Keywords: Yager Model, FMADM, FMODM, FMCDM, fuzzy decision-making.

Multi-Objective Optimization Based Multi-Objective Controller Tuning Method with Robust Stabilization of Fractional Calculus CSTR

2021 ◽  
Vol 16 ◽  
pp. 375-382
Author(s):  
T. Sudha
Keyword(s):  
Decision Making ◽  
Fractional Order ◽  
Pid Controller ◽  
Genetic Evaluation ◽  
Performance Estimation ◽  
Multi Criteria Decision Making ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Flower Pollination ◽  
Fractional Order Pid

In Continuous Stirred Tank Reactor (CSTR) have Fractional order PID with the nominal order PID controller has been used to Multi-Criteria Decision Making (MCDM) and EMO (Evolutionary Multi-objective Optimization) by adjustment of control parameters like Hybrid methods in Multi objective optimization. But, this Fractional order PID with the nominal PID controller has maximum performance estimation. Proposed research work focused the Flower Pollination Algorithm based on Multi objective optimization with Genetic evaluation and Fractional order PID with the nominal PID controller is provides CSTR results. When a flower is displayed to maximum variations in this practical state, the Genetic evaluation has been used to identify the variations. The FPID (Flower Pollination Integral Derivative) is used for tuning the parameters of a Fractional order PID with the nominal PID controller for each region to improve the multi-criteria decision making. FPID also denoted as Flower Optimization Integral Derivative (FOID). The Genetic evaluation scheduler has been combined with multiple local linear Fractional order PID with the nominal PID controller to check the stability of loop for entire regions with various levels of temperatures. MATLAB results demonstrate that the feasibility of using the proposed Fractional order PID with the nominal PID controller compared than the existing PID controller, and it shows the FOID attained better results.

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