scholarly journals MULTI-OBJECTIVE OPTIMIZATION APPLIED FOR PLANNING OF REGIONAL EUROPEAN AIRLINE

2014 ◽  
Vol 29 (1) ◽  
pp. 37-46 ◽  
Author(s):  
Andrzej Majka
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Decision Problem ◽  
Planning Process ◽  
Transportation System ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Fleet Planning

Fleet planning is very important elements in the airlines planning process. Fleet planning should answer the question which types of aircraft are required and how many of them are required taking into account the current and future transportation needs. Decision-making in the field of operations has a character of engineering. This process requires consideration of many factors, dependencies and criteria. The article presents the decision problem formulated in the form of a multi-objective mathematical model. This work preliminarily determines the structure of the transportation system which performs carriages on the local routes.

scholarly journals A Multi-Objective Decision-Making Framework for Transportation Investments

2010 ◽  
Author(s):  
Mashrur Chowdhury ◽  
Pulin Tan
Keyword(s):  
Decision Making ◽  
Decision Problem ◽  
Discrete Problem ◽  
Multi Objective Optimization ◽  
Trade Off ◽  
Multi Objective ◽  
Transportation Investment ◽  
Continuous Problems ◽  
Decision Making Framework

This paper presents a framework based on multi-objective optimization that can be used to generate and analyze the most desirable transportation investment options based on their objectives and constraints. The framework, which is based on the surrogate worth trade-off analysis, could be applied to both discrete or continuous decision-problem scenarios. In a discrete problem, a pre-defined set of alternatives is available, whereas continuous problems are not characterized by a pre-defined set of alternatives. This framework was applied with the data generated for a Capital Beltway Corridor investment study. The multi-objective decision-making framework was found to be adaptable to this typical investment case study.

Multi-objective optimization for safety and reliability trade-off: Optimization and results processing

2018 ◽  
Vol 232 (6) ◽  
pp. 661-676
Author(s):  
Cristina Johansson ◽  
Johan Ölvander ◽  
Micael Derelöv
Keyword(s):  
Decision Making ◽  
Solid Base ◽  
Multi Objective Optimization ◽  
Specific System ◽  
Multi Objective ◽  
Trade Offs ◽  
Design Alternatives ◽  
Safety And Reliability ◽  
Potential Issue ◽  
Selection Of

In early design phases, it is vital to be able to screen the design space for a set of promising design alternatives for further study. This article presents a method able to balance several objectives of different mathematical natures, with high impact on the design choices. The method (MOSART) handles multi-objective optimization for safety and reliability trade-offs. The article focuses on optimization problem approach and processing of results as a base for decision-making. The output of the optimization step is the selection of specific system elements obtaining the best balance between the targets. However, what is a good base for decision can easily transform into too much information and overloading of the decision-maker. To solve this potential issue, from a set of Pareto optimal solutions, a smaller sub-set of selected solutions are visualized and filtered out using preference levels of the objectives, yielding a solid base for decision-making and valuable information on potential solutions. Trends were observed regarding each system element and discussed while processing the results of the analysis, supporting the decision of one final best solution.

A Method for Solving Multi-Objective Optimization Problems Containing an Infinite Number of Parameterized Objectives

2020 ◽  
Author(s):  
Eliot Rudnick-Cohen
Keyword(s):  
Decision Making ◽  
Infinite Number ◽  
Optimization Problems ◽  
Pareto Frontier ◽  
Brute Force ◽  
Multi Objective Optimization ◽  
New Approach ◽  
Multi Objective ◽  
Brute Force Approach ◽  
Better Than

Abstract Multi-objective decision making problems can sometimes involve an infinite number of objectives. In this paper, an approach is presented for solving multi-objective optimization problems containing an infinite number of parameterized objectives, termed “infinite objective optimization”. A formulation is given for infinite objective optimization problems and an approach for checking whether a Pareto frontier is a solution to this formulation is detailed. Using this approach, a new sampling based approach is developed for solving infinite objective optimization problems. The new approach is tested on several different example problems and is shown to be faster and perform better than a brute force approach.

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