Promoting objective knowledge transfer: A cascaded fuzzy system for solving dynamic multiobjective optimization problems
In this article, a novel dynamic multiobjective optimization algorithm (DMOA) with a
cascaded fuzzy system (CFS) is developed, which aims to promote objective knowledge …
cascaded fuzzy system (CFS) is developed, which aims to promote objective knowledge …
A novel planning method for design and dispatch of hybrid energy systems
F Ren, X Lin, Z Wei, X Zhai, J Yang - Applied Energy, 2022 - Elsevier
The hybrid energy systems that integrate renewable technologies with natural gas combined
cooling, heating and power technologies are an excellent way to provide low-carbon energy …
cooling, heating and power technologies are an excellent way to provide low-carbon energy …
An enhance multimodal multiobjective optimization genetic algorithm with special crowding distance for pulmonary hypertension feature selection
Multiobjective optimization assumes a one-to-one map** between decisions and
objective space, however, this is not always the case. When many variables have the same …
objective space, however, this is not always the case. When many variables have the same …
Evolutionary algorithms for parameter optimization—thirty years later
Thirty years, 1993–2023, is a huge time frame in science. We address some major
developments in the field of evolutionary algorithms, with applications in parameter …
developments in the field of evolutionary algorithms, with applications in parameter …
Optimisation of remanufacturing supply chain with dual recycling channels under improved deep reinforcement learning algorithm
Z Wang, C Ye, J Guo - … Journal of Systems Science: Operations & …, 2024 - Taylor & Francis
To address the challenge of reducing carbon emissions in the automotive industry, new
energy vehicles (NEVs) have emerged, leading to an increase in the number of discarded …
energy vehicles (NEVs) have emerged, leading to an increase in the number of discarded …
A fast nondominated sorting-based MOEA with convergence and diversity adjusted adaptively
In the past few decades, to solve the multi-objective optimization problems, many multi-
objective evolutionary algorithms (MOEAs) have been proposed. However, MOEAs have a …
objective evolutionary algorithms (MOEAs) have been proposed. However, MOEAs have a …
Regularity evolution for multiobjective optimization
Recent years have witnessed the repaid progress in develo** and applying multiobjective
evolutionary algorithms (MOEAs). However, as a major component of an MOEA, the …
evolutionary algorithms (MOEAs). However, as a major component of an MOEA, the …
A parallel approximate evaluation-based model for multi-objective operation optimization of reservoir group
D Liu, T Bai, M Deng, Q Huang, X Wei, J Liu - Swarm and Evolutionary …, 2023 - Elsevier
Reservoir operation optimization can boost the efficiency of water resources utilization, but
sometimes has huge search space and time-consuming calculation. Approximate evaluation …
sometimes has huge search space and time-consuming calculation. Approximate evaluation …
A two-stage planning method for design and dispatch of distributed energy networks considering multiple energy trading
F Ren, X Lin, X Ma, Z Wei, R Wang, X Zhai - Sustainable Cities and Society, 2023 - Elsevier
Distributed energy network integrated by distributed energy system has significant
performance advantages due to energy sources sharing. However, the incorporation of …
performance advantages due to energy sources sharing. However, the incorporation of …
A meta-heuristic algorithm combined with deep reinforcement learning for multi-sensor positioning layout problem in complex environment
Y Ning, Z Bai, J Wei, PN Suganthan, L **ng… - Expert Systems with …, 2025 - Elsevier
In a multi-sensor positioning system (MSPS), the layout of sensors plays a crucial role in
determining the system's performance. Therefore, addressing the sensor layout problem …
determining the system's performance. Therefore, addressing the sensor layout problem …