Results 191 to 200 of about 12,208,333 (235)
Some of the next articles are maybe not open access.
A Tradeoff Cut Approach to Multiple Objective Optimization
Operations Research, 1980There is a need to develop user-oriented math programming techniques for resolution of decision problems in which several objectives must be considered. One approach, the Geoffrion-Dyer-Feinberg algorithm, allows interaction between the computer and the decision maker during the solution process.
K. Musselman, Joseph J. Talavage
openaire +1 more source
Multiple-objective optimization applied in extracting multiple-choice tests
Engineering Applications of Artificial Intelligence, 2021Abstract Student evaluation is an essential part of education and is usually done through examinations. These examinations generally use tests consisting of several questions as crucial factors to determine the quality of the students. Test-making can be thought of as a multi-constraint optimization problem.
Tram Nguyen +6 more
openaire +1 more source
MOEA/D for Multiple Multi-objective Optimization
2021This paper defines a new multi-objective optimization problem, called multiple multi-objective optimization problem (MMOP). An MMOP is composed of several multi-objective optimization problems (MOPs) with different decision spaces and the same objective space, and its optimal solutions are non-dominated solutions among Pareto optimal solutions of all ...
Jingjing Chen +2 more
openaire +2 more sources
Grillage Optimization with Multiple Objectives
Key Engineering Materials, 2006The structural design problems are acknowledged to be commonly multicriteria in nature. The various multicriteria optimization methods are reviewed and the most efficient and easy-to-use Pareto optimal solution methods are applied to structural optimization of grillages under lateral uniform load.
Ki Sung Kim, Kyung Su Kim, Ki Sup Hong
openaire +1 more source
Multiple Objective Optimization
2020In this chapter, we discuss the differences between a MOOP and a SOOP and present the weighted sum approach and the e-constraint method to solve convex MOOPs formulated as multi-objective linear optimization problems (MOLPs). Moreover, we highlight the fundamental principles of multi-objective optimization and present a way to explore the Pareto ...
openaire +1 more source
On multiple-objective optimal designs
Journal of Statistical Planning and Inference, 2019zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cheng, Qianshun, Yang, Min
openaire +2 more sources
Handling multiple objectives with biogeography-based optimization
International Journal of Automation and Computing, 2012Biogeography-based optimization (BBO) is a new evolutionary optimization method inspired by biogeography. In this paper, BBO is extended to a multi-objective optimization, and a biogeography-based multi-objective optimization (BBMO) is introduced, which uses the cluster attribute of islands to naturally decompose the problem.
Hai-Ping Ma, Xieyong Ruan, Zhang-Xin Pan
openaire +2 more sources
Special issue on global optimization with multiple objectives
Journal of Global Optimization, 2015This special issue devoted to global optimization with multiple objectives contains five carefully reviewed papers. Three of them are related to presentations given at the 22nd International Conference on Multiple Criteria Decision Making (MCDM)which was held in Malaga, Spain, in June 17–21, 2013. Biennial international conferences on MCDM are the main
Kaisa Miettinen +3 more
openaire +1 more source
Kriging metamodeling in multiple-objective simulation optimization
SIMULATION, 2011This paper describes the application of Kriging metamodeling in multiple-objective simulation optimization. An Arena-based simulation model of an (s, S) inventory system is utilized to demonstrate the capabilities of Kriging metamodeling as a simulation tool. Response surface methodology and Kriging metamodeling are compared to determine the situations
Mehdi Zakerifar +2 more
openaire +1 more source
Hiding sensitive itemsets with multiple objective optimization
Soft Computing, 2019Privacy-preserving data mining (PPDM) has become an important research topic, as it can hide sensitive information, while ensuring that information can still be extracted for decision making. While performing the sanitization progress for hiding the sensitive information, three side effects such as hiding failure, missing cost, and artificial cost ...
Jerry Chun-Wei Lin +4 more
openaire +2 more sources