scholarly journals Multiobjective Optimization of Aircraft Maintenance in Thailand Using Goal Programming: A Decision-Support Model

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
Yuttapong Pleumpirom ◽  
Sataporn Amornsawadwatana
Keyword(s):  
Decision Support ◽  
Multiobjective Optimization ◽  
Goal Programming ◽  
Optimization Model ◽  
Decision Support Tool ◽  
Spare Part ◽  
Aircraft Maintenance ◽  
Decision Support Model ◽  
Support Tool ◽  
Flight Schedules

The purpose of this paper is to develop the multiobjective optimization model in order to evaluate suppliers for aircraft maintenance tasks, using goal programming. The authors have developed a two-step process. The model will firstly be used as a decision-support tool for managing demand, by using aircraft and flight schedules to evaluate and generate aircraft-maintenance requirements, including spare-part lists. Secondly, they develop a multiobjective optimization model by minimizing cost, minimizing lead time, and maximizing the quality under various constraints in the model. Finally, the model is implemented in the actual airline's case.

scholarly journals The benefits of action to reduce household air pollution (BAR-HAP) model: A new decision support tool

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245729
Author(s):  
Ipsita Das ◽  
Jessica J. Lewis ◽  
Ramona Ludolph ◽  
Melanie Bertram ◽  
Heather Adair-Rohani ◽  
...  
Keyword(s):  
Air Pollution ◽  
Decision Support ◽  
Decision Support Tool ◽  
Global Scale ◽  
Household Air Pollution ◽  
Large Set ◽  
Costs And Benefits ◽  
Decision Support Model ◽  
Support Tool ◽  
Policy Interventions

Cooking with polluting and inefficient fuels and technologies is responsible for a large set of global harms, ranging from health and time losses among the billions of people who are energy poor, to environmental degradation at a regional and global scale. This paper presents a new decision-support model–the BAR-HAP Tool–that is aimed at guiding planning of policy interventions to accelerate transitions towards cleaner cooking fuels and technologies. The conceptual model behind BAR-HAP lies in a framework of costs and benefits that is holistic and comprehensive, allows consideration of multiple policy interventions (subsidies, financing, bans, and behavior change communication), and realistically accounts for partial adoption and use of improved cooking technology. It incorporates evidence from recent efforts to characterize the relevant set of parameters that determine those costs and benefits, including those related to intervention effectiveness. Practical aspects of the tool were modified based on feedback from a pilot testing workshop with multisectoral users in Nepal. To demonstrate the functionality of the BAR-HAP tool, we present illustrative calculations related to several cooking transitions in the context of Nepal. In accounting for the multifaceted nature of the issue of household air pollution, the BAR-HAP model is expected to facilitate cross-sector dialogue and problem-solving to address this major health, environment and development challenge.

scholarly journals Sistem Pendukung Keputusan Pengalokasian Spare Part

2013 ◽  
Vol 6 (1) ◽  
Author(s):  
Rita Wiryasaputra ◽  
Sri Hartati
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Maker ◽  
Goal Programming ◽  
Spare Part ◽  
Entropy Method ◽  
Ideal Solution ◽  
Decision Support Model ◽  
Main Concept ◽  
Conflicting Objectives

AbstrakEra informasi yang semakin berkembang mempengaruhi lingkungan bisnis. Pengaruhnya dapat dilihat pada proses pengambilan keputusan. Proses pengambilan keputusan terhadap sejumlah alternatif dan sejumlah tujuan diselesaikan dengan sebuah sistem. Sistem  yang bermodelkan Multi Attribute Decision Making (MADM) dan Multi Objective Decision Making (MODM). Model MODM digunakan untuk menyelesaikan perancangan alternatif terbaik dan model MADM digunakan untuk menyelesaikan penyeleksian terhadap beberapa alternatif dalam jumlah yang terbatas. Salah satu pendekatan model MADM adalah TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Konsep utama TOPSIS adalah alternatif preferensi terbaik memiliki jarak terpendek dari solusi ideal positif dan memiliki jarak terjauh dari solusi ideal negatif. Hasil metode TOPSIS adalah perankingan terhadap sejumlah alternatif. Salah satu masukan dari metode TOPSIS adalah nilai pembobotan kriteria. Nilai pembobotan kriteria dapat diberikan secara langsung oleh pengambil keputusan atau dihitung melalui sebuah metode. Penelitian akan menghitung nilai pembobotan kriteria dengan metode Entropy. Tujuannya adalah untuk memberikan objektifitas pembobotan kriteria. Penelitian mengangkat kasus tentang pengalokasian spare part ke sejumlah store. Alternatif terbaik dengan sumber daya yang terbatas, beberapa tujuan yang saling bertentangan didekati dengan metode Goal programming. Pengambilan keputusan akan lebih terarah karena sistem menghasilkan perankingan store spare part, dan menampilkan  informasi alokasi spare part.  Kata kunci— Sistem Pendukung Keputusan, Entropy, TOPSIS, Goal Programming AbstractThe capabilities of computrized systems facilitate decision support in a number of ways, such as speed computations, increased productivity ,improved data management and others. Decisions are often made by individuals. There may be conflicting objectives even for a  decision maker. The conflicting objectives can be solved by goal programming. Research of spare part allocation focuses on an individual decision maker and presents the solving problem with Multiple Criteria Decision Making (MCDM). A lot of MCDM approaches have been developed and applied to diverse fields, like engineering, management, economic, etc. As one of the known classical MCDM approaches, TOPSIS method is known to be a common method to get the preliminary outcome.  The main concept of TOPSIS is the best alternative has the shortest distance from the positive ideal solution and has the longest distance from the negative ideal solution.  Before the stores are ranked with TOPIS method, the management assigned a weightage to each store using Entropy method.  Keywords— Decision Support Model, Entropy, TOPSIS, Goal Programming.

A Decision Support Tool for Evaluating Big Data Investment in Transport: Empirical evidence from European use cases of NOESIS project

2020 ◽  
Author(s):  
Christos Katrakazas ◽  
Natalia Sobrino ◽  
Ilias Trochidis ◽  
Jose Manuel Vassallo ◽  
Stratos Arampatzis ◽  
...  
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Empirical Evidence ◽  
Decision Support Tool ◽  
Use Cases ◽  
Support Tool
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