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Hybrid multi-objective genetic algorithm for multi-objective optimization problems
The 27th Chinese Control and Decision Conference (2015 CCDC), 2015As a result of important practical significance in real-world engineering applications, multi-objective optimization problem has been one of scientific problems concerned by many researchers. In recent years, genetic algorithm (GA) has begun to be widely used to solve a variety of multi-objective optimization problems due to its population-based search
Song Zhang +3 more
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Multi-objective Optimization Problem
2017This chapter discusses general aspects regarding multi-objective optimization. For this purpose, the state of the art is presented, considering basic concepts and definitions, mathematical formulation, optimality conditions, metrics for convergence and diversity, and methodologies to solve this kind of problem are discussed.
Fran Sérgio Lobato, Valder Steffen
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Scalable multi-objective optimization test problems
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600), 2003After adequately demonstrating the ability to solve different two-objective optimization problems, multi-objective evolutionary algorithms (MOEAs) must show their efficacy in handling problems having more than two objectives. In this paper, we suggest three different approaches for systematically designing test problems for this purpose. The simplicity
K. Deb +3 more
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Multi-objective Trajectory Optimization Problem
2019In this chapter, the SMV trajectory optimization problem established in the previous chapter is reformulated and extended to a multi-objective continuous-time optimal control model. Because of the discontinuity or nonlinearity in the vehicle dynamics and mission objectives, it is challenging to generate a compromised trajectory that can satisfy ...
Runqi Chai +3 more
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Loney's solenoid multi-objective optimization problem
IEEE Transactions on Magnetics, 1999A multi-objective optimization problem for Loney's solenoid consists of the determination of the current system which produces a uniform magnetic field within a domain of finite extent inside the solenoid and a low stray field outside it. In order to solve the multi-objective problem, four different approaches have been utilized and compared.
C. A. BORGHI +3 more
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Localization for Solving Noisy Multi-Objective Optimization Problems
Evolutionary Computation, 2009This paper investigates the use of a framework of local models in the context of noisy evolutionary multi-objective optimization. Within this framework, the search space is explicitly divided into several nonoverlapping hyperspheres. A direction of improvement, which is related to the average performance of the spheres, is used for moving solutions ...
Lam T, Bui +2 more
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Treatment of Multi-objective Optimization Problem
2017In this chapter, the treatment of multi-objective optimization problems considering Classical Aggregation Methods and both Deterministic and Non-Deterministic Methods is presented. In addition, a brief review about the treatment of constraints and heuristic approaches associated with dominance concept are also discussed.
Fran Sérgio Lobato, Valder Steffen
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Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation, 2014
Hypervolume has been frequently used as an indicator to evaluate a solution set in indicator-based evolutionary algorithms (IBEAs). One important issue in such an IBEA is the choice of a reference point. A different solution set is often obtained from a different reference point since the hypervolume calculation depends on the location of the reference
Hisao Ishibuchi +2 more
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Hypervolume has been frequently used as an indicator to evaluate a solution set in indicator-based evolutionary algorithms (IBEAs). One important issue in such an IBEA is the choice of a reference point. A different solution set is often obtained from a different reference point since the hypervolume calculation depends on the location of the reference
Hisao Ishibuchi +2 more
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Knowledge-Based Systems, 2018
Abstract This paper proposes a multi-objective version of recently developed Spotted Hyena Optimizer (SHO) called Multi-objective Spotted Hyena Optimizer (MOSHO). It is used to optimize the multiple objectives problems. In the proposed algorithm, a fixed-sized archive is employed for storing the non-dominated Pareto optimal solutions.
Gaurav Dhiman, Vijay Kumar
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Abstract This paper proposes a multi-objective version of recently developed Spotted Hyena Optimizer (SHO) called Multi-objective Spotted Hyena Optimizer (MOSHO). It is used to optimize the multiple objectives problems. In the proposed algorithm, a fixed-sized archive is employed for storing the non-dominated Pareto optimal solutions.
Gaurav Dhiman, Vijay Kumar
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Multi-objective ordinal optimization for simulation optimization problems
Automatica, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Teng, S., Hay Lee, L., Peng Chew, E.
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