A novel epsilon-dominance Harris Hawks optimizer for multi-objective optimization in engineering design problems

Allou, Lotfi; Zouache, Djaafar; Amroun, Kamal; Got, Adel

doi:10.1007/s00521-022-07352-9

Cited by 11 publications

(4 citation statements)

References 30 publications

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“…The four-bar plane truss design problem has been widely used to evaluate and verify the engineering application potential of the algorithm [55][56][57] . This problem contains four joint points and four structural members, takes the cross-sectional area of the structural members as the design variables, and takes the synchronous minimization of the volume of the plane truss and the vertical displacement of the node as the optimization objective functions.…”

Section: Application Experimentsmentioning

confidence: 99%

Adaptive Sampling Immune Algorithm for Multi-Objective Probabilistic Optimization

Zhang,

Pan,

Zhang

2024

Preprint

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In this paper, for a general type of multi-objective probabilistic optimization problem without any prior noisy information, which has an extensive engineering application background and needs to be solved urgently, we propose a small-population immune algorithm with adaptive sampling to solve. In the design. First, we design a small-population immune algorithm framework inspired by the response mechanism of adaptive immunity. Second, we design an adaptive sampling scheme that adaptively allocates an appropriate number of samples for each sub-objective function of all individuals in the population to estimate the objective function value. Third, based on the objective function estimates, the dominance levels of all individuals in the population and the crowding distances of individuals in each dominance level are determined. Fourth, the clone size, mutation rate, crossover distribution index, and mutation distribution index of an individual are designed to be adaptively determined based on the number of iterations, dominance level, and crowding distance. Cloning, crossover, and mutation operators are implemented for each individual, using simulated binary crossover and polynomial mutation to enhance co-evolution and facilitate information sharing and exchange among all individuals. Fifth, based on the dominance level and crowding distance, the population update strategies are designed to adaptively update the memory set with high-quality individuals and generate a new generation population with good diversity. Finally, based on three theoretical problems and two engineering problems, as well as six representative comparative algorithms, the experimental results show that the proposed algorithm is an optimizer with good competitiveness and application potential, and has few parameters, less sample consumption, strong noise suppression ability, and high search efficiency.

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Section: Application Experimentsmentioning

confidence: 99%

Adaptive Sampling Immune Algorithm for Multi-Objective Probabilistic Optimization

Zhang,

Pan,

Zhang

2024

Preprint

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“…

is the set of feasible solutions, which is formed by the intersection of the constraints of the optimization problem [21] . We denote the image of the decision space by

and we call it an objective space [22] . The elements of

, are called objective vectors and they consist of real-valued objective functions.…”

Section: Preliminariesmentioning

confidence: 99%

A decomposition-based multiobjective evolutionary algorithm using Simulated Annealing for the ambulance dispatching and relocation problem during COVID-19

Hemici

Zouache

Brahmi

et al. 2023

Applied Soft Computing

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“…If , , and negative threshold constraints do not exist, then this criterion is established and is represented by . In this paper, a five-level domination criterion is constructed by adding or reducing the constraints of partial binary relations based on the classical multi-attribute decision making theory [39]. Negative threshold constraints are added to the fourth-level and fifth-level domination criteria to prevent outranking relations with gaps that are too large from being screened out.…”

Section: Fig 2 General Framework Of the Pne-prtc Algorithmmentioning

confidence: 99%

Multicriteria Game Approach to Air-to-Air Combat Tactical Decisions for Multiple UAVs

Jiang,

Luo,

et al. 2023

J. of Syst. Eng. Electron.

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Air-to-air combat tactical decisions for multiple unmanned aerial vehicles (ACTDMU) are a key decision-making step in beyond visual range combat. Complex influencing factors, strong antagonism and real-time requirements need to be considered in the ACTDMU problem. In this paper, we propose a multicriteria game approach to ACTDMU. This approach consists of a multicriteria game model and a Pareto Nash equilibrium algorithm. In this model, we form the strategy profiles for the integration of air-to-air combat tactics and weapon target assignment strategies by considering the correlation between them, and we design the vector payoff functions based on predominance factors. We propose a algorithm of Pareto Nash equilibrium based on preference relations using threshold constraints (PNE-PRTC), and we prove that the solutions obtained by this algorithm are refinements of Pareto Nash equilibrium solutions. The numerical experiments indicate that PNE-PRTC algorithm is considerably faster than the baseline algorithms and the performance is better. Especially on large-scale instances, the Pareto Nash equilibrium solutions can be calculated by PNE-PRTC algorithm at the second level. The simulation experiments show that the multicriteria game approach is more effective than one-side decision approaches such as multiple-attribute decision-making and randomly chosen decisions.

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A novel epsilon-dominance Harris Hawks optimizer for multi-objective optimization in engineering design problems

Cited by 11 publications

References 30 publications

Adaptive Sampling Immune Algorithm for Multi-Objective Probabilistic Optimization

Adaptive Sampling Immune Algorithm for Multi-Objective Probabilistic Optimization

A decomposition-based multiobjective evolutionary algorithm using Simulated Annealing for the ambulance dispatching and relocation problem during COVID-19

Multicriteria Game Approach to Air-to-Air Combat Tactical Decisions for Multiple UAVs

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