scholarly journals E-NAUTILUS: A decision support system for complex multiobjective optimization problems based on the NAUTILUS method

2015 ◽  
Vol 246 (1) ◽  
pp. 218-231 ◽  
Author(s):  
Ana B. Ruiz ◽  
Karthik Sindhya ◽  
Kaisa Miettinen ◽  
Francisco Ruiz ◽  
Mariano Luque
Keyword(s):  
Decision Support ◽  
Multiobjective Optimization ◽  
Decision Support System ◽  
Support System ◽  
Optimization Problems ◽  
Multiobjective Optimization Problems

Development of Neural-Net-Based Decision Support System for Mattress Patterns Using Particle Swarm Optimization

2010 ◽  
Vol 4 (2) ◽  
pp. 178-183 ◽  
Author(s):  
Mitsue Kato ◽  
◽  
Toru Yamamoto ◽  
Keyword(s):  
Particle Swarm Optimization ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Optimization Problems ◽  
Learning Algorithm ◽  
Particle Swarm ◽  
Neural Net ◽  
Swarm Optimization ◽  
Neural Network Learning

The particle swarm optimization (PSO) concept simulating a simplified social milieu, is optimization useful for solving nonconvex continuous optimization problems. We discuss a new learning algorithm for simultaneously adjusting connection weights in neural networks and user-specified parameters included in units. Based on our algorithm, neural network learning, e.g., learning cost or adaptability, can be improved, as demonstrated in mattress decision support system.

Research of Decision Support Technologies in Multi-Dimensional Data Environment

2012 ◽  
Vol 214 ◽  
pp. 601-604
Author(s):  
Ze Guo Qiu
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Data Warehouse ◽  
Support System ◽  
Data Model ◽  
Optimization Problems ◽  
Data Combination ◽  
Data Environment ◽  
Decision Support Technology

In this paper, further research has been done on the relevant decision support technology in the multi-dimensional data environment, including decision support system, the environment of multi-dimensional data model, multi-dimensional data combination problems based on data warehouse optimization problems and overall structure, etc.

Web-Based Decision Support System for Solving Multiple-Objective Decision-Making Problems

2019 ◽  
pp. 150-175 ◽  
Author(s):  
Leoneed Kirilov ◽  
Vassil Guliashki ◽  
Boris Staykov
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Optimization Problems ◽  
Solution Process ◽  
Multiple Objective ◽  
Core System ◽  
Web Based ◽  
Multiple Objective Decision Making ◽  
Basic Characteristics

A web-based Decision Support System WebOptim for solving multiple objective optimization problems is presented. The system WebOptim is designed in a modular principle, extensively using XML as communication standard and web services. Its basic characteristics are: user-independent, multisolver-admissibility, method-independent, heterogeneity, web-accessibility. Core system module is an original generalized interactive scalarizing method. It incorporates a number of thirteen interactive methods. Most of the known scalarizing approaches (reference point approach, reference direction approach, classification approach etc.) are realized in this method. The Decision Maker (DM) can choose the most suitable for him/her form for setting his/her preferences: objective weights, aspiration levels, aspiration directions, aspiration intervals. This information could be changed interactively by the DM during the solution process. Depending on the DM's preferences form the suitable scalarizing method is chosen automatically. The chapter begins with an overview of Decision Support Systems (DSS). Examples of DSSs and their applications are discussed.

Web-Based Decision Support System for Solving Multiple-Objective Decision-Making Problems

2021 ◽  
pp. 594-620
Author(s):  
Leoneed Kirilov ◽  
Vassil Guliashki ◽  
Boris Staykov
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Optimization Problems ◽  
Solution Process ◽  
Multiple Objective ◽  
Core System ◽  
Web Based ◽  
Multiple Objective Decision Making ◽  
Basic Characteristics

A web-based Decision Support System WebOptim for solving multiple objective optimization problems is presented. The system WebOptim is designed in a modular principle, extensively using XML as communication standard and web services. Its basic characteristics are: user-independent, multisolver-admissibility, method-independent, heterogeneity, web-accessibility. Core system module is an original generalized interactive scalarizing method. It incorporates a number of thirteen interactive methods. Most of the known scalarizing approaches (reference point approach, reference direction approach, classification approach etc.) are realized in this method. The Decision Maker (DM) can choose the most suitable for him/her form for setting his/her preferences: objective weights, aspiration levels, aspiration directions, aspiration intervals. This information could be changed interactively by the DM during the solution process. Depending on the DM's preferences form the suitable scalarizing method is chosen automatically. The chapter begins with an overview of Decision Support Systems (DSS). Examples of DSSs and their applications are discussed.

scholarly journals A Tri-Layer Optimization Framework for Day-Ahead Energy Scheduling Based on Cost and Discomfort Minimization

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3599
Author(s):  
Paraskevas Koukaras ◽  
Paschalis Gkaidatzis ◽  
Napoleon Bezas ◽  
Tommaso Bragatto ◽  
Federico Carere ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Energy Management ◽  
Support System ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Cost Minimization ◽  
Optimization Framework ◽  
Optimal Energy ◽  
Optimal Energy Management

Over the past few decades, industry and academia have made great strides to improve aspects related with optimal energy management. These include better ways for efficient energy asset management, generating great opportunities for optimization of energy distribution, discomfort minimization, energy production, cost reduction and more. This paper proposes a framework for a multi-objective analysis, acting as a novel tool that offers responses for optimal energy management through a decision support system. The novelty is in the structure of the methodology, since it considers two distinct optimization problems for two actors, consumers and aggregators, with solution being able to completely or partly interact with the other one is in the form of a demand response signal exchange. The overall optimization is formulated by a bi-objective optimization problem for the consumer side, aiming at cost minimization and discomfort reduction, and a single objective optimization problem for the aggregator side aiming at cost minimization. The framework consists of three architectural layers, namely, the consumer, aggregator and decision support system (DSS), forming a tri-layer optimization framework with multiple interacting objects, such as objective functions, variables, constants and constraints. The DSS layer is responsible for decision support by forecasting the day-ahead energy management requirements. The main purpose of this study is to achieve optimal management of energy resources, considering both aggregator and consumer preferences and goals, whilst abiding with real-world system constraints. This is conducted through detailed simulations using real data from a pilot, that is part of Terni Distribution System portfolio.

Decision Support System Development Based On Android Using Analytical Hierarchy Process (AHP) Method For Determining The Middle Small Business Development Priority In Sorong City

2019 ◽  
Vol 5 (2) ◽  
pp. 25-39
Author(s):  
Luluk Suryani ◽  
Raditya Faisal Waliulu ◽  
Ery Murniyasih
Keyword(s):  
Decision Support ◽  
Small Business ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
System Development ◽  
Business Development ◽  
Ahp Method ◽  
Small Business Development ◽  
Hierarchy Process

Usaha Kecil Menengah (UKM) adalah salah satu penggerak perekonomian suatu daerah, termasuk Kota Sorong. UKM di Kota Sorong belum berkembang secara optimal. Ada beberapa penyebab diantaranya adalah mengenai finansial, lokasi, bahan baku dan lain-lain. Untuk menyelesaikan permasalah tersebut peneliti terdorong untuk melakukan pengembangan Aplikasi yang dapat membantu menentukan prioritas UKM yang sesuai dengan kondisi pelaku usaha. Pada penelitian ini akan digunakan metode Analitycal Hierarchy Process (AHP), untuk pengambilan keputusannya. Metode AHP dipilih karena mampu menyeleksi dan menentukan alternatif terbaik dari sejumlah alternatif yang tersedia. Dalam hal ini alternatif yang dimaksudkan yaitu UKM terbaik yang dapat dipilih oleh pelaku usaha sesuai dengan kriteria yang telah ditentukan. Penelitian dilakukan dengan mencari nilai bobot untuk setiap atribut, kemudian dilakukan proses perankingan yang akan menentukan alternatif yang optimal, yaitu UKM. Aplikasi Sistem Pendukung Keputusan yang dikembangkan berbasis Android, dimana pengguna akan mudah menggunakannya sewaktu-waktu jika terjadi perubahan bobot pada kriteria atau intensitas.  Hasil akhir menunjukkan bahwa metode AHP berhasil diterapkan pada Aplikasi Penentuan Prioritas Pengembangan UKM.

Sign in / Sign up

Export Citation Format

Share Document