Results 11 to 20 of about 6,112,119 (319)
IEEE Access, 2021 A well-designed demand response (DR) program is essential in smart home to optimize energy usage according to user preferences. In this study, we proposed a multiobjective reinforcement learning (MORL) algorithm to design a DR program.
Song-Jen Chen, Wei-Yu Chiu, Wei-Jen Liu
doaj +1 more source
CoRR, 2022 We study the problem of generating diverse candidates in the context of Multi-Objective Optimization. In many applications of machine learning such as drug discovery and material design, the goal is to generate candidates which simultaneously optimize a set of potentially conflicting objectives.
Moksh Jain +6 more
openaire +3 more sources
IEEE Access, 2022 Snake-like modular robots (MRs) are highly flexible, but, to traverse a challenging terrain or explore a region of interest, MR needs to attain efficient locomotion depending on a tradeoff between objectives like forward velocity and power consumption of
Akash Singh +3 more
doaj +1 more source
IEEE Access, 2023 In this paper, a quality diversity optimization method (QDOM) based on an adaptive bound-searching algorithm and diversity-selecting immune algorithm is proposed for solving bilinear matrix inequality (BMI) problems in control system design. By using the
Shiuan-Yeh Chen +2 more
doaj +1 more source
Multi objective project portfolio selection [PDF]
Journal of Project Management, 2019 The Project Portfolio Selection is a complex process that involves many factors and considerations since the project is proposed until the project portfolio is finally selected.
Kamal Baqeri +2 more
doaj +1 more source
IET Generation, Transmission & Distribution, 2023 With the increasing rate of population in big cities around the world, the tendency to build new buildings in the suburb of main cities or to build large apartments in the main cities has been highlighted.
Mehdi Davoudi +2 more
doaj +1 more source
IET Generation, Transmission & Distribution, 2023 An Optimal power flow (OPF) is non‐linear and constrained multi‐objective problem. OPF problems are expensive and evolutionary algorithms (EAs) are computationally complex to obtain uniformly distributed and global Pareto front (PF).
Aamir Ali +5 more
doaj +1 more source
Multi-objective congestion control
Proceedings of the Seventeenth European Conference on Computer Systems, 2022 Decades of research on Internet congestion control (CC) has produced a plethora of algorithms that optimize for different performance objectives. Applications face the challenge of choosing the most suitable algorithm based on their needs, and it takes tremendous efforts and expertise to customize CC algorithms when new demands emerge.
Yiqing Ma +6 more
openaire +2 more sources
MOMPA: Multi-objective marine predator algorithm for solving multi-objective optimization problems
, 2021 This paper proposes a new multi-objective algorithm, called Multi-Objective Marine-Predator Algorithm (MOMPA), dependent on elitist non-dominated sorting and crowding distance mechanism.
Jangir, Pradeep +3 more
core +1 more source
Multi-objective multi-criteria evolutionary algorithm for multi-objective multi-task optimization
Complex & Intelligent Systems, 2022 Evolutionary multi-objective multi-task optimization is an emerging paradigm for solving multi-objective multi-task optimization problem (MO-MTOP) using evolutionary computation.
Ke-Jing Du +3 more
doaj +1 more source