This study proposes a robust method to improve the search performance of multi-objective
evolutionary algorithms (MOEAs) using a Pareto-based archiving mechanism and a …

Degradation modeling and prognostics serve as the basis for system health management.
Recently, various sensors provide plentiful monitoring data that can reflect the system status …

The tradeoff between objective functions and constraints is a key issue that needs to be
addressed by constrained multiobjective optimization algorithms, and constraint handling …

Despite increasing incentives, the practice of separating process design and control tasks
remains prevalent. Current integrated approaches, when coupled with controller design …

The solving of large-scale multi-objective optimization problem (LSMOP) has become a hot
research topic in evolutionary computation. To better solve this problem, this paper proposes …

Hundreds or thousands of decision variables are involved in large-scale multi-objective
optimization problems (LSMOPs), which may include scheduling and artificial intelligence …

Closed loop layout problem (CLLP) is an important class of design problems encountered in
flexible manufacturing system. It is to determine the locations of manufacturing cells along a …

A differential evolution (DE) algorithm with superior-inferior mutation scheme (SIDE) is
proposed to solve global optimization problems over continuous space. Firstly, a superior …

Evolutionary algorithms have shown great successes in various real-world applications
ranging in molecule to astronomy. As a mainstream evolutionary algorithm, differential …

This paper introduces a new control theory for optimizing anti-lock braking systems (ABS) in
automotive applications. Anti-lock systems play a critical role in ensuring vehicle safety …