A comprehensive review on multi-objective optimization techniques: Past, present and future
Realistic problems typically have many conflicting objectives. Therefore, it is instinctive to
look at the engineering problems as multi-objective optimization problems. This paper briefly …
look at the engineering problems as multi-objective optimization problems. This paper briefly …
Computational intelligence in remote sensing image registration: A survey
In recent years, computational intelligence has been widely used in many fields and
achieved remarkable performance. Evolutionary computing and deep learning are important …
achieved remarkable performance. Evolutionary computing and deep learning are important …
Multi-objective equilibrium optimizer: Framework and development for solving multi-objective optimization problems
This paper proposes a new Multi-Objective Equilibrium Optimizer (MOEO) to handle
complex optimization problems, including real-world engineering design optimization …
complex optimization problems, including real-world engineering design optimization …
Multi-objective optimisation for energy-aware flexible job-shop scheduling problem with assembly operations
W Ren, J Wen, Y Yan, Y Hu, Y Guan… - International Journal of …, 2021 - Taylor & Francis
There is a lack of studies on joint optimisation of flexible job-shop scheduling problem
(FJSP) considering energy consumption and production efficiency in the machining …
(FJSP) considering energy consumption and production efficiency in the machining …
Multi-objective exponential distribution optimizer (MOEDO): a novel math-inspired multi-objective algorithm for global optimization and real-world engineering design …
The exponential distribution optimizer (EDO) represents a heuristic approach, capitalizing
on exponential distribution theory to identify global solutions for complex optimization …
on exponential distribution theory to identify global solutions for complex optimization …
A multi-objective chaos game optimization algorithm based on decomposition and random learning mechanisms for numerical optimization
Abstract Chaos Game Optimization (CGO) is a heuristic optimization approach that
estimates global optima for optimization problems using operators based on chaos theory …
estimates global optima for optimization problems using operators based on chaos theory …
Revenue and energy cost-optimized biobjective task scheduling for green cloud data centers
The significant growth in the number and types of tasks of heterogeneous applications in
green cloud data centers (GCDCs) dramatically increases their providers' revenue from …
green cloud data centers (GCDCs) dramatically increases their providers' revenue from …
An automated health indicator construction methodology for prognostics based on multi-criteria optimization
In recent years, the development of autonomous health management systems received
increasing attention from worldwide companies to improve their performances and avoid …
increasing attention from worldwide companies to improve their performances and avoid …
A multi-objective instance-based decision support system for investment recommendation in peer-to-peer lending
G Babaei, S Bamdad - Expert Systems with Applications, 2020 - Elsevier
Abstract Peer-to-peer (P2P) lending has attracted many investors and borrowers since 2005.
This financial market helps investors and borrowers to invest in or get loans without a …
This financial market helps investors and borrowers to invest in or get loans without a …
Multi-objective resistance-capacitance optimization algorithm: An effective multi-objective algorithm for engineering design problems
Focusing on practical engineering applications, this study introduces the Multi-Objective
Resistance-Capacitance Optimization Algorithm (MORCOA), a new approach for multi …
Resistance-Capacitance Optimization Algorithm (MORCOA), a new approach for multi …