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Multiobjective Optimization for the Stochastic Physical Search Problem
[chapter]
2015
Lecture Notes in Computer Science
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We model an intelligence collection activity as multiobjective optimization on a binary stochastic physical search problem, providing formal definitions of the problem space and nondominated solution sets ...
We present the Iterative Domination Solver as an approximate method for generating solution sets that can be used by a human decision maker to meet the goals of a mission. ...
Problem formulation We formulate the AS-ISR problem as a stochastic physical search problem (SPSP), where we are given an undirected network G(S + , E) with a set of sites S + = S ∪ {o, d} where S = {s ...
doi:10.1007/978-3-319-19066-2_21
fatcat:sbbnvkjnfzfuxpkrw2vypmauci
Efficient Hybrid Multiobjective Optimization of Pressure Swing Adsorption
2021
Chemical Engineering Journal
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In the first step, a Bayesian stochastic multiobjective optimization algorithm (i.e., TSEMO) searches the entire decision space and identifies an approximated Pareto front within a small number of simulations ...
A B S T R A C T Pressure swing adsorption (PSA) is an energy-efficient technology for gas separation, while the multiobjective optimization of PSA is a challenging task. ...
Tobias Ploch (RWTH Aachen) for helping to debug the PSA model in Dymola. ...
doi:10.1016/j.cej.2021.130248
fatcat:vt5shizmaneklgerpzvmd374lu
Stochastic Fractal Based Multiobjective Fruit Fly Optimization
2017
International Journal of Applied Mathematics and Computer Science
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In this study, a novel stochastic fractal model based fruit fly optimization algorithm is proposed for multiobjective optimization. ...
To deal with multiobjective optimization problems, the Pareto domination concept is integrated into the selection process of fruit fly optimization and a novel multiobjective fruit fly optimization algorithm ...
Acknowledgment This work was partly supported by the National Natural Science ...
doi:10.1515/amcs-2017-0029
fatcat:huzywkjtxzf3veylfs4prx7fyq
A new competitive multiverse optimization technique for solving single‐objective and multiobjective problems
2020
Engineering Reports
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The development of useful algorithms for solving global optimization problems has recently drawing the research community's attention. ...
In this work, a novel population-based optimization technique is proposed, the so-called competitive multiverse optimizer (CMVO) for solving global optimization problems. ...
approaches that are not stochastic (ie, dependent on the problem), metaheuristics optimize problems gradually and stochastically find the optimal solution (ie, independent on the problem). ...
doi:10.1002/eng2.12124
fatcat:eg6hepznvjcdzcg5raj7facmqe
Dingo Optimizer: A Nature-Inspired Metaheuristic Approach for Engineering Problems
2021
Mathematical Problems in Engineering
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Optimization is a buzzword, whenever researchers think of engineering problems. ...
Some of the well-known test functions are used for the comparative study of this work. The results reveal that the dingo optimizer performed significantly better than other nature-inspired algorithms. ...
(HS) [37] Multiobjective HS [38] Tabu search (TS) [39] Multiobjective TS [40] Parameter adaptive harmony search (PAHS) [41] Multiobjective PAHS [41] Group search optimizer (GSO) [42] Multiobjective ...
doi:10.1155/2021/2571863
fatcat:gvws4rhidneljoasxcm5372qky
Multiobjective evolutionary algorithms: A survey of the state of the art
2011
Swarm and Evolutionary Computation
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for multimodal problems, constraint handling and MOEAs, computationally expensive multiobjective optimization problems (MOPs), dynamic MOPs, noisy MOPs, combinatorial and discrete MOPs, benchmark problems ...
A multiobjective optimization problem involves several conflicting objectives and has a set of Pareto optimal solutions. ...
Jaszkiewicz [79] proposed a multiobjective genetic local search (MOGLS) algorithm for the multiobjective 0/1 knapsack problem. ...
doi:10.1016/j.swevo.2011.03.001
fatcat:jfcghitjp5ap5he4d3ackhhjsu
Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis
2017
Journal of Engineering
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The exhaustive knowledge of optimal power flow (OPF) methods is critical for proper system operation and planning, since OPF methods are utilized for finding the optimal state of any system under system ...
Incorporating renewable energy sources optimized the power flow of system under different constraints. ...
Conflicts of Interest The authors declare that there are no conflicts of interest regarding the publication of this paper. ...
doi:10.1155/2017/9539506
fatcat:ybh7nsn7ybdkng6756pjxey5je
IS-PAES: A Constraint-Handling Technique Based on Multiobjective Optimization Concepts
[chapter]
2003
Lecture Notes in Computer Science
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shrinking the constrained space of single-objective optimization problems. ...
This paper introduces a new constraint-handling method called Inverted-Shrinkable PAES (IS-PAES), which focuses the search effort of an evolutionary algorithm on specific areas of the feasible region by ...
The first author acknowledges support from CONACyT project I-39324-A. The second author acknowledges support from CONACyT project No. 34575-A. ...
doi:10.1007/3-540-36970-8_6
fatcat:sqfiynbazbftxef4zkntj55osq
A hierarchical evolutionary algorithm for multiobjective optimization in IMRT
2010
Medical Physics (Lancaster)
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The MOEA incorporates clinical criteria to restrict the search space through protocol objectives and then uses Pareto optimality among the fitness objectives to select individuals. ...
Results: Acceleration techniques implemented on both levels of the hierarchical algorithm resulted in short, practical runtimes for optimizations. ...
A multiobjective optimization ͑MOO͒ algorithm is one method for searching through the space of feasible plans. ...
doi:10.1118/1.3478276
pmid:20964218
pmcid:PMC2945740
fatcat:pksdvtiyf5a43g3ijgkvsczo6q
Antenna Optimization Using Multiobjective Algorithms
2012
ISRN Communications and Networking
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This paper presents several applications of multiobjective optimization to antenna design, emphasizing the main general steps in this process. ...
Both stochastic and deterministic methods are considered in the analysis. ...
However, most of the problems can be divided into search for optimal solutions and approximate solution of Maxwell's equations using numerical methods. ...
doi:10.5402/2012/369293
fatcat:rmn74urlfjdjvp4u5mcajnkg6q
Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design
2021
International Conference on Machine Learning
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We propose a new formulation that accounts for the importance of the parameter space and is thus more suitable for multiobjective design problems; instead of searching for the Paretoefficient frontier, ...
Sample-efficient multiobjective optimization methods focus on the objective function values in metric space and ignore the sampling behavior of the design configurations in parameter space. ...
Acknowledgements We want to thank Sajad Haghanifar and Paul Leu for providing the scanning electron microscope images and motivating the research presented in this paper. ...
dblp:conf/icml/MalkomesCLM21
fatcat:5zpy2d4qu5eexn56wun7pflxni
Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm
2015
Journal of Applied Mathematics
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In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. ...
Solving a nonlinear multiobjective optimization problem requires significant computing effort. ...
The multiobjective disc brake optimization problem was solved by Osyczka and Kundu [21] using plain stochastic method and genetic algorithms for optimization of disc brake problem. ...
doi:10.1155/2015/165601
fatcat:ey22323t65drplxapshdy6l2uq
Multivariate Stochastic Optimization Approach Applied in a Flux-Cored Arc Welding Process
2020
IEEE Access
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The weighting-sums method was applied to formulate the multiobjective optimization problem. It was possible to formulate a multivariate probability distribution for the penetration and dilution. ...
However, several optimization problems that use stochastic programming do not consider the impact of the correlation between the output variables on their probabilistic constraints. ...
for the multiobjective optimization problem. ...
doi:10.1109/access.2020.2983566
fatcat:fggobmmen5bkrfixffsdef3giy
The Application of Multiobjective Genetic Algorithm to the Parameter Optimization of Single-Well Potential Stochastic Resonance Algorithm Aimed at Simultaneous Determination of Multiple Weak Chromatographic Peaks
2014
The Scientific World Journal
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Therefore, multiobjective genetic algorithm was employed to optimize the parameter of SSRA for multiple optimization objectives (i.e.,S/Nand peak shape) and multiple chromatographic peaks. ...
However, the optimization of the parameters is complicated and time consuming, although the single-well potential stochastic resonance algorithm (SSRA) has already reduced the number of parameters to only ...
GAs can search for many noninferior solutions in parallel by maintaining a population of solutions. Therefore, GAs are very suitable for solving the problems of multiobjective optimization [23] . ...
doi:10.1155/2014/767018
pmid:24526920
pmcid:PMC3913510
fatcat:n5zxtnxok5hvrpeztengpex26q
Advances and challenges of quantitative verification and synthesis for cyber-physical systems
2016
2016 Science of Security for Cyber-Physical Systems Workshop (SOSCYPS)
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to support the design process, and hence improve the reliability and reduce production costs. ...
This paper gives an overview of quantitative verification and synthesis techniques developed for cyber-physical systems, summarising recent achievements and future challenges in this important field. ...
The parameter synthesis problem aims to find an optimal value of the parameter that guarantees the satisfaction of a quantitative temporal logic property. ...
doi:10.1109/soscyps.2016.7579999
dblp:conf/cpsweek/Kwiatkowska16
fatcat:ugbkizf4xrcgzjvgtutecnepuu
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