On Solving the Multi-Objective Software Package Upgradability Problem

Free and open source software (FOSS) distributions are increasingly based on the abstraction of packages to manage and accommodate new features before and after the deployment stage. However, due to inter-package dependencies, package upgrade entails challenging shortcomings of deployment and management of complex software systems, inhibiting their ability to cope with frequent upgrade failures. Moreover, the upgrade process may be achieved according to some criteria (maximize the stability, minimize outdated packages, etc.). This problem is actually a multi-objective optimization problem. Throughout the article, the authors propose a Leximax approach based on mixed integer linear programming (MILP) to tackle the upgradability problem, while ensuring efficiency and fairness requirements between the objective functions. Experiments performed on real-world instances, from the MANCOOSI project, show that the authors' approach efficiently finds solutions of consistently high quality.

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Braille Block Detection via Multi-Objective Optimization from an Egocentric Viewpoint

Sensors ◽

10.3390/s21082775 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2775

Author(s):

Tsubasa Takano ◽

Takumi Nakane ◽

Takuya Akashi ◽

Chao Zhang

Keyword(s):

Optimization Problem ◽

Line Pair ◽

Objective Functions ◽

Multi Objective Optimization ◽

Multi Objective ◽

Optimization Framework ◽

Visually Impaired People ◽

Comprehensive Comparison ◽

Basic Characteristics ◽

Support Devices

In this paper, we propose a method to detect Braille blocks from an egocentric viewpoint, which is a key part of many walking support devices for visually impaired people. Our main contribution is to cast this task as a multi-objective optimization problem and exploits both the geometric and the appearance features for detection. Specifically, two objective functions were designed under an evolutionary optimization framework with a line pair modeled as an individual (i.e., solution). Both of the objectives follow the basic characteristics of the Braille blocks, which aim to clarify the boundaries and estimate the likelihood of the Braille block surface. Our proposed method was assessed by an originally collected and annotated dataset under real scenarios. Both quantitative and qualitative experimental results show that the proposed method can detect Braille blocks under various environments. We also provide a comprehensive comparison of the detection performance with respect to different multi-objective optimization algorithms.

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MULTI-OBJECTIVE OPTIMIZATION WITH OPTIMAL COMBINATION CRITERIA s APPLIED TO DETERMINE FREEZE DRYING REGIME FOR CRUSTACEAN GROUP (PENAEUS MONODON)

Science and Technology Development Journal ◽

10.32508/stdj.v13i2.2118 ◽

2010 ◽

Vol 13 (2) ◽

pp. 59-71

Author(s):

Dzung Tan Nguyen ◽

Hai Xuan Le ◽

Dzung Van Trinh

Keyword(s):

Freeze Drying ◽

Optimization Problem ◽

Penaeus Monodon ◽

Objective Functions ◽

Multi Objective Optimization ◽

Technological Regime ◽

Multi Objective ◽

Energy Expenditures ◽

Temperature And Pressure ◽

Drying Regime

This article presents research results from the freeze drying regime for penaeus monodon based-on the solution of the multi-objective optimization problem. Experiments were carried out to determine the objective functions to describe influence of technological parametres (temperature and pressure of sublimation environment, times of freeze drying) during processing freeze drying. The multi-objective optimization problem was solved by Utopian point method with combination criteria s. The best technological regime for freeze drying was determined. At received freeze drying regime we have minimal energy expenditures, minimal contraction of product and minimal loss of vitamin c, humidity of material meet requirements from 2 to 6 percentage and maximal absorbent return of product.

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Design of Pareto-Optimal Radar Receive Filters

International Journal of Electronics and Telecommunications ◽

10.2478/v10177-011-0067-y ◽

2011 ◽

Vol 57 (4) ◽

pp. 477-481 ◽

Cited By ~ 11

Author(s):

Antonio De Maio ◽

Marco Piezzo ◽

Salvatore Iommelli ◽

Alfonso Farina

Keyword(s):

Quadratic Forms ◽

Optimization Problem ◽

Pareto Optimal ◽

Relative Importance ◽

Objective Functions ◽

Multi Objective Optimization ◽

Sidelobe Level ◽

Multi Objective ◽

Optimal Theory ◽

Peak Sidelobe Level

Design of Pareto-Optimal Radar Receive Filters This paper deals with the design of radar receive filters jointly optimized with respect to sidelobe energy and sidelobe peaks via Pareto-optimal theory. We prove that this criterion is tantamount to jointly minimizing two quadratic forms, so that the design can be analytically formulated in terms of a multi-objective optimization problem. In order to solve it, we resort to the scalarization technique, which reduces the vectorial problem into a scalar one using a Pareto weight defining the relative importance of the two objective functions. At the analysis stage, we assess the performance of the receive filters in correspondence of different values of the Pareto weight highlighting the performance compromises between the Integrated Sidelobe Level (ISL) and the Peak Sidelobe Level (PSL).

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A Decision-Making Tool for a Complex Post Enrollment-Based Course Timetabling

Journal of Southwest Jiaotong University ◽

10.35741/issn.0258-2724.55.6.2 ◽

2020 ◽

Vol 55 (6) ◽

Author(s):

Ngo Tung Son

Keyword(s):

Combinatorial Problems ◽

Mixed Integer ◽

Objective Functions ◽

Multi Objective Optimization ◽

Spring Semester ◽

Multi Objective ◽

Training Costs ◽

Proposed Model ◽

Decision Making Tool ◽

Single Objective

The article describes a new method to construct an enrollment-based course timetable in universities, based on a multi-objective optimization model. The model used mixed-integer and binary variables towards creating a schedule. It satisfies students' preferences for study time, with the number of students in the same class being optimal for training costs while ensuring timetabling business constraints. We use a combination of compromise programming and linear scalarizing to transform many objective functions into single-objective optimization. A scheme of the Genetic Algorithm was developed to solve the proposed model. The proposed method allows approaching several types of multi-objective combinatorial problems. The algorithm was tested by scheduling a study schedule for 3,000 students in the spring semester of 2020 at FPT University, Hanoi, Vietnam. The obtained results show the average students' preference level of 69%. More than 30% of students have a satisfaction level of more than 80% of the timetable after two hours of execution time.

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MULTI-OBJECTIVE OPTIMIZATION WITH OPTIMAL STANDARD COMBINATION OF R APPLIED TO DETERMINE REGIME TECHNOLOGICAL FREEZE DRYING OF PENAEUS MERGUIENSIS

Science and Technology Development Journal ◽

10.32508/stdj.v13i2.2112 ◽

2010 ◽

Vol 13 (2) ◽

pp. 66-75

Author(s):

Dzung Tan Nguyen ◽

Hai Xuan Le ◽

Dzung Van Trinh

Keyword(s):

Freeze Drying ◽

Optimization Problem ◽

Minimum Energy ◽

Objective Functions ◽

Multi Objective Optimization ◽

Optimal Regime ◽

Multi Objective ◽

Energy Expenditures ◽

Vitamine C ◽

Penaeus Merguiensis

This article presents research results of determinative regime technological freeze drying of Penaeus Merguiensis by method to solve a multi-Objective optimization problem with optimal standard combination of R. Experimental research was carried out building objective functions to describe influence of technological element (temperature of sublimation environment, pressure of sublimation environment and times of freeze drying) during processing freeze drying. By restricted zone (optimal standard combination of R) method determined optimal regime technological freeze drying have minimum energy expenditures/1 kg product, minimum humidity of material, maximum absorbent return of product, minimum contraction of product and minimum loss of vitamine c.

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An Interval-Based Approach for Evolutionary Multi-Objective Optimization of Project Portfolios

International Journal of Information Technology & Decision Making ◽

10.1142/s021962201950024x ◽

2019 ◽

Vol 18 (04) ◽

pp. 1317-1358 ◽

Cited By ~ 4

Author(s):

Fausto Balderas ◽

Eduardo Fernandez ◽

Claudia Gomez-Santillan ◽

Nelson Rangel-Valdez ◽

Laura Cruz

Keyword(s):

Optimization Problem ◽

Pareto Frontier ◽

Region Of Interest ◽

Project Portfolio ◽

Objective Functions ◽

Multi Objective Optimization ◽

Public Project ◽

Multi Objective ◽

Imperfect Knowledge ◽

Project Portfolios

Project portfolio selection is addressed here as a multi-objective optimization problem. This work introduces an interval-based method that takes into consideration imperfect knowledge of the contribution of projects to a portfolio, the project requirements, available resources and preference parameters in the model. The multi-objective optimization problem is solved using an evolutionary algorithm that is adapted to handle intervals. To direct the search toward the region of interest of the Pareto frontier, the preferences of the decision maker (DM) are incorporated using an interval-based outranking approach. This allows to address problems with many objective functions; intransitive preferences and incomparability situations can also be handled using this approach. In terms of analyzing robustness, the DM can obtain different solutions according to his/her level of conservatism. The effectiveness of this proposal was tested both on an example from the related literature and another example of a public project portfolio with nine objective functions and large number of applicant projects.

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Design Optimization of a Twist Compliant Mechanism With Nonlinear Stiffness

Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting ◽

10.1115/smasis2013-3031 ◽

2013 ◽

Cited By ~ 3

Author(s):

Yashwanth Tummala ◽

Mary Frecker ◽

Aimy Wissa ◽

James E. Hubbard

Keyword(s):

Optimization Problem ◽

Inner Core ◽

Compliant Mechanism ◽

Twist Angle ◽

Von Mises Stress ◽

Nonlinear Stiffness ◽

Objective Functions ◽

Multi Objective Optimization ◽

Multi Objective ◽

Specific Loading

A contact aided compliant mechanism called twist compliant mechanism is presented in this paper. This mechanism has nonlinear stiffness when it is twisted in both directions along its axis. The inner core of the mechanism is responsible for its flexibility in one twisting direction. The contact surfaces of the cross-members and compliant sectors are responsible for its high stiffness in the opposite direction. A twist compliant mechanism with desired twist angle and stiffness can be designed by choosing the right thickness of its cross-members, thickness of the core and thickness of its sectors. A multi-objective optimization problem with three objective functions is proposed in this paper, and used to design an optimal twist compliant mechanism with desired deflection. The objective functions are to minimize the mass and maximum von Mises stress observed, while minimizing or maximizing the twist angles under specific loading conditions. The multi-objective optimization problem proposed in this paper is solved using an ornithopter flight research platform as a case study, with the goal of using the twist compliant mechanism to achieve passive twisting of the wing during upstroke, while keeping the wing fully extended and rigid during the downstroke. Prototype twist compliant mechanisms have been fabricated using a waterjet cutter and will be tested as part of future work.

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MULTI-OBJECTIVE OPTIMAL REACTIVE POWER DISPATCH USING DIFFERENTIAL EVOLUTION

International Journal of Engineering Technologies and Management Research ◽

10.29121/ijetmr.v6.i2.2019.353 ◽

2020 ◽

Vol 6 (2) ◽

pp. 27-38 ◽

Cited By ~ 2

Author(s):

Ram Kishan Mahate ◽

Himmat Singh

Keyword(s):

Differential Evolution ◽

Optimization Problem ◽

Reactive Power ◽

Discrete Control ◽

Mixed Integer ◽

Multi Objective Optimization ◽

Power Sources ◽

Multi Objective ◽

Power Dispatch ◽

Reactive Power Dispatch

Reactive power optimization is a major concern in the operation and control of power systems. In this paper a new multi-objective differential evolution method is employed to optimize the reactive power dispatch problem. It is the mixed–integer non linear optimization problem with continuous and discrete control variables such as generator terminal voltages, tap position of transformers and reactive power sources. The optimal VAR dispatch problem is developed as a nonlinear constrained multi objective optimization problem where the real power loss and fuel cost are to be minimized at the same time. A conventional weighted sum method is inflicted to provide the decision maker with a example and accomplishable Pareto-optimal set. This method underlines non-dominated solutions and at the same time asserts diversity in the non-dominated solutions. Thus this technique treats the problem as a true multi-objective optimization problem. The performance of the suggested differential evolution approach has been tested on the standard test system IEEE 30-bus.

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An Efficient Framework for Multi-Objective Risk-Informed Decision Support Systems for Drainage Rehabilitation

Mathematical and Computational Applications ◽

10.3390/mca25040073 ◽

2020 ◽

Vol 25 (4) ◽

pp. 73

Author(s):

Xiatong Cai ◽

Abdolmajid Mohammadian ◽

Hamidreza Shirkhani

Keyword(s):

Optimization Problems ◽

Drainage System ◽

Mixed Integer ◽

Engineering Optimization ◽

Continuous Variables ◽

Objective Functions ◽

Multi Objective Optimization ◽

Integer Optimization ◽

Framework Structure ◽

Multi Objective

Combining multiple modules into one framework is a key step in modelling a complex system. In this study, rather than focusing on modifying a specific model, we studied the performance of different calculation structures in a multi-objective optimization framework. The Hydraulic and Risk Combined Model (HRCM) combines hydraulic performance and pipe breaking risk in a drainage system to provide optimal rehabilitation strategies. We evaluated different framework structures for the HRCM model. The results showed that the conventional framework structure used in engineering optimization research, which includes (1) constraint functions; (2) objective functions; and (3) multi-objective optimization, is inefficient for drainage rehabilitation problem. It was shown that the conventional framework can be significantly improved in terms of calculation speed and cost-effectiveness by removing the constraint function and adding more objective functions. The results indicated that the model performance improved remarkably, while the calculation speed was not changed substantially. In addition, we found that the mixed-integer optimization can decrease the optimization performance compared to using continuous variables and adding a post-processing module at the last stage to remove the unsatisfying results. This study (i) highlights the importance of the framework structure inefficiently solving engineering problems, and (ii) provides a simplified efficient framework for engineering optimization problems.

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