A decision support approach for two-stage multi-objective index tracking using improved lagrangian decomposition

Omega ◽  
2020 ◽  
Vol 91 ◽  
pp. 102017 ◽  
Author(s):  
Dexiang Wu ◽  
Desheng Dash Wu
Keyword(s):  
Decision Support ◽  
Index Tracking ◽  
Lagrangian Decomposition ◽  
Two Stage ◽  
Multi Objective

scholarly journals Multi-Objective Two-Stage Stochastic Programming Model for a Proposed Casualty Transportation System in Large-Scale Disasters: A Case Study

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 316
Author(s):  
Nadide Caglayan ◽  
Sule Itir Satoglu
Keyword(s):  
Decision Support ◽  
Stochastic Programming ◽  
Programming Model ◽  
Decision Support Tool ◽  
Data Driven ◽  
Two Stage ◽  
Support Tool ◽  
Transportation Time ◽  
Multi Objective ◽  
Stochastic Programming Model

Disaster management is a process that includes mitigation, preparedness, response and recovery stages. Operational strategies covering all stages must be developed in order to alleviate the negative effects of the disasters. In this study, we aimed at minimizing the number of casualties that could not be transported to the hospitals after the disaster, the number of additional ambulances required in the response stage, and the total transportation time. Besides, we assumed that a data-driven decision support tool is employed to track casualties and up-to-date hospital capacities, so as to direct the ambulances to the available hospitals. For this purpose, a multi-objective two-stage stochastic programming model was developed. The model was applied to a district in Istanbul city of Turkey, for a major earthquake. Accordingly, the model was developed with a holistic perspective with multiple objectives, periods and locations. The developed multi-objective stochastic programming model was solved using an improved version of the augmented ε-constraint (AUGMECON2) method. Hence, the Pareto optimal solutions set has been obtained and compared with the best solution achieved according to the objective of total transportation time, to see the effect of the ambulance direction decisions based on hospital capacity availability. All of the decisions examined in these comparisons were evaluated in terms of effectiveness and equity. Finally, managerial implication strategies were presented to contribute decision-makers according to the results obtained. Results showed that without implementing a data-driven decision support tool, equity in casualty transportation cannot be achieved among the demand points.

Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Initial Step ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Prospective Students ◽  
Multi Objective

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.

scholarly journals A Two-Stage Mono- and Multi-Objective Method for the Optimization of General UPS Parallel Manipulators

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 543
Author(s):  
Alejandra Ríos ◽  
Eusebio E. Hernández ◽  
S. Ivvan Valdez
Keyword(s):  
Genetic Algorithm ◽  
Performance Metrics ◽  
Tracking Error ◽  
Parallel Manipulators ◽  
Optimization Method ◽  
Statistical Hypothesis ◽  
Two Stage ◽  
Multi Objective ◽  
Second Stage ◽  
Conflicting Objectives

This paper introduces a two-stage method based on bio-inspired algorithms for the design optimization of a class of general Stewart platforms. The first stage performs a mono-objective optimization in order to reach, with sufficient dexterity, a regular target workspace while minimizing the elements’ lengths. For this optimization problem, we compare three bio-inspired algorithms: the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), and the Boltzman Univariate Marginal Distribution Algorithm (BUMDA). The second stage looks for the most suitable gains of a Proportional Integral Derivative (PID) control via the minimization of two conflicting objectives: one based on energy consumption and the tracking error of a target trajectory. To this effect, we compare two multi-objective algorithms: the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) and Non-dominated Sorting Genetic Algorithm-III (NSGA-III). The main contributions lie in the optimization model, the proposal of a two-stage optimization method, and the findings of the performance of different bio-inspired algorithms for each stage. Furthermore, we show optimized designs delivered by the proposed method and provide directions for the best-performing algorithms through performance metrics and statistical hypothesis tests.

A two-stage evolutionary strategy based MOEA/D to multi-objective problems

2021 ◽  
pp. 115654
Author(s):  
Jie Cao ◽  
Jianlin Zhang ◽  
Fuqing Zhao ◽  
Zuohan Chen
Keyword(s):  
Evolutionary Strategy ◽  
Two Stage ◽  
Multi Objective

scholarly journals Sistem Bantu untuk Pengrajin dalam Menentukan Kayu Terbaik Terbaik untuk Bahan Gitar dengan Menggunakan Matode Moora

2021 ◽  
Vol 8 (6) ◽  
pp. 1177
Author(s):  
Tundo Tundo ◽  
Wisnu Dwi Nugroho
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
A Value ◽  
Wood Grain ◽  
The Right ◽  
Moora Method

<p>Penelitian ini bertujuan untuk membantu pengrajin kayu di Dongkelan, Krapyak, Yogyakarta dalam menentukan kayu terbaik untuk dijadikan sebagai bahan gitar, karena sering terjadi keluhan dari para pembeli bahwa bahan yang dijadikan bahan gitar cepat lapuk dan kusam dari segi warnah. Berdasarkan permasalahan tersebut, dicari suatu solusi dengan menggunakan metode <em>Decision Support System</em> <em>Multi Objective Optimization on the basic of Ratio Analysis</em><em> </em>(MOORA) serta dibantu oleh pakar dalam menentukan kriteria yang tepat berkaitan penentuan kayu terbaik yang digunakan dalam pembuatan bahan gitar, setelah berdiskusi panjang ditemukan hasil kriteria yang tepat berdasarkan permasalahan, berupa kriteria kekuatan kayu, serat kayu, tekstur, dan berat kayu. Semua kriteria tersebut, kemudian diproses dengan menggunakan metode MOORA, dengan data yang digunakan sebanyak 29 jenis data kayu, yang diperoleh dari pengrajin yang ada di wilayah tersebut. Setelah diproses, diperoleh hasil 3 kayu terbaik yang layak untuk digunakan sebagai bahan pembuatan gitar secara berurutan dalah kayu Bubinga dengan nilai 18,36785, kayu Bocote dengan nilai 17,33385, dan kayu Eboni dengan nilai 17,33385   dari beberapa pilihan alternatif  kayu yang ada. Membuktikan hasil dari metode MOORA<em>, </em>maka dilakukan responden secara langsung dengan memberikan hasil metode kepada pakar pembuat gitar. Dari 15 pakar pembuat gitar, 13 mengatakan setuju dengan peringkat 3 terbesar, dan 2 mengatakan kurang setuju. Sehingga ditemukan tingkat akurasi berdasarkan penilaian pakar sebesar 86,67 %.</p><p> </p><p><strong>Abstract</strong></p><div><p><em>This study aims to assist wood craftsmen in Dongkelan, Krapyak, Yogyakarta in determining the best wood to be used as guitar material, because there are frequent complaints from buyers that the material used for guitar is rotten quickly and is dull in terms of color. Based on these problems, a solution was sought using the Multi Objective Optimization on the basic of Ratio Analysis (MOORA) Decision Support System method and assisted by experts in determining the right criteria related to determining the best wood used in making guitar materials, after a long discussion found the results. the right criteria based on the problem, in the form of wood strength criteria, wood grain, texture, and wood weight. All of these criteria are then processed using the MOORA method, with the data used as much as 29 types of wood data, which are obtained from craftsmen in the area. After processing, the 3 best woods that are suitable for use as a guitar-making material are Bubinga wood with a value of 18.36785, Bocote wood with a value of 17.333385, and Eboni wood with a value of 17.333385 from several alternative wood choices. . Proving the results of the MOORA method, the respondents directly gave the results of the method to guitar-making experts. Of the 15 expert guitar makers, 13 said they agreed with the third largest ranking, and 2 said they disagreed. So that it found the level of accuracy based on expert judgment of 86.67%. </em></p></div><p><strong><br /></strong></p>

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