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Werry Febrianti, Kuntjoro Adji Sidarto and Novriana Sumarti
Portfolio optimization is an activity for balancing return and risk. In this paper, we used mean-variance (M-V) portfolio models with buy-in threshold and cardinality constraints. This model can be formulated as a mixed integer nonlinear programming (MIN...
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Wendy Wijaya and Kuntjoro Adji Sidarto
Portfolio optimization is a mathematical formulation whose objective is to maximize returns while minimizing risks. A great deal of improvement in portfolio optimization models has been made, including the addition of practical constraints. As the number...
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Adekunle Rotimi Adekoya and Mardé Helbig
Dynamic multi-objective optimization problems (DMOPs) are optimization problems where elements of the problems, such as the objective functions and/or constraints, change with time. These problems are characterized by two or more objective functions, whe...
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Gangxuan Hu, Guohui Zhang, Yanyan Li, Xun Wang, Jiping An, Zhibin Zhang and Xinhong Li
The modular self-reconfigurable satellites (MSRSs) are a new type of satellite that can transform configuration in orbit autonomously. The inverse kinematics of MSRS is difficult to solve by conventional methods due to the hyper-redundant degrees of free...
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Rong Bao, Yongdong Li, Hongguang Wang and Chunliang Liu
The current design period for various backward wave oscillators (BWOs) is still at least several months. How to find the best structure parameters with an efficient and stable optimization method is a problem facing researchers in both scientific researc...
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Carlos Camacho-Gomez, Rocio Sanchez-Montero, Diego Martínez-Villanueva, Pablo-Luís López-Espí and Sancho Salcedo-Sanz
A novel textile U-shaped with concentric annular slot antenna prototype for LTE and 5G services has been described. In the ground plane, a meander slot has been introduced to reduce the antenna dimensions. A new multi-method metaheuristic algorithm, the ...
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Alexey Vakhnin and Evgenii Sopov
Many modern real-valued optimization tasks use ?black-box? (BB) models for evaluating objective functions and they are high-dimensional and constrained. Using common classifications, we can identify them as constrained large-scale global optimization (cL...
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Dinita Rahmalia,Teguh Herlambang,Thomy Eko Saputro
Pág. 120 - 130
Background: The applications of constrained optimization have been developed in many problems. One of them is production planning. Production planning is the important part for controlling the cost spent by the company.Objective: This research identifies...
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Konstantinos Gkiotsalitis and Rahul Kumar
In public transport operations, vehicles tend to bunch together due to the instability of passenger demand and traffic conditions. Fluctuation of the expected waiting times of passengers at bus stops due to bus bunching is perceived as service unreliabil...
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Paulo Rotela Junior, Luiz Célio Souza Rocha, Giancarlo Aquila, Edson de Oliveira Pamplona, Pedro Paulo Balestrassi, Anderson Paulo de Paiva
Pág. 623 - 631
The objective of this paper is to present a proposal to form robust portfolios using a stochastic efficiency analysis of assets from companies in the Sao Paulo Stock Exchange, focusing on the worst market state. In order to do this, information about the...
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Shih-Cheng Horng and Shieh-Shing Lin
The stochastic inequality constrained optimization problems (SICOPs) consider the problems of optimizing an objective function involving stochastic inequality constraints. The SICOPs belong to a category of NP-hard problems in terms of computational comp...
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Tamás Kegyes, Alex Kummer, Zoltán Süle and János Abonyi
We analyzed a special class of graph traversal problems, where the distances are stochastic, and the agent is restricted to take a limited range in one go. We showed that both constrained shortest Hamiltonian pathfinding problems and disassembly line bal...
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Pedro Fernandes, Àlex Ferrer, Paulo Gonçalves, Marco Parente, Ricardo Pinto and Nuno Correia
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José D. Hoyos, Jesús H. Jiménez, Camilo Echavarría, Juan P. Alvarado and Germán Urrea
An aero-structural algorithm to reduce the energy consumption of a propeller-driven aircraft is developed through a propeller design method coupled with a Particle Swarm Optimization (PSO). A wide range of propeller parameters is considered in the optimi...
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Rebekah Herrman, Lorna Treffert, James Ostrowski, Phillip C. Lotshaw, Travis S. Humble and George Siopsis
We develop a global variable substitution method that reduces n-variable monomials in combinatorial optimization problems to equivalent instances with monomials in fewer variables. We apply this technique to 3-SAT and analyze the optimal quantum unitary ...
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Tingting Pan, Yu Zhang, Fenzhen Su, Vincent Lyne, Fei Cheng and Han Xiao
Practical efficient regional land-use planning requires planners to balance competing uses, regional policies, spatial compatibilities, and priorities across the social, economic, and ecological domains. Genetic algorithm optimization has progressed comp...
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Ruobing Xue, Xiangshen Ye and Weiping Wu
In this paper we study the optimization of the discrete-time stochastic linear-quadratic (LQ) control problem with conic control constraints on an infinite horizon, considering multiplicative noises. Stochastic control systems can be formulated as Markov...
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Yiyuan Sun, Qiang Wang, Kevin Tansey, Sana Ullah, Fan Liu, Haimeng Zhao and Lei Yan
Image-based line segment extraction plays an important role in a wide range of applications. Traditional line segment extraction algorithms focus on the accuracy and efficiency, without considering the integrity. Serious line segmentation fracture proble...
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Syed Waqas Haider Shah, Khalid Iqbal and Ahmad Talal Riaz
The Internet-of-Things (IoT) is a paradigm shift from slow and manual approaches to fast and automated systems. It has been deployed for various use-cases and applications in recent times. There are many aspects of IoT that can be used for the assistance...
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Syed Waqas Haider Shah, Khalid Iqbal and Ahmad Talal Riaz
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