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Alireza Rezvanian, S. Mehdi Vahidipour and Ali Mohammad Saghiri
Artificial immune systems (AIS), as nature-inspired algorithms, have been developed to solve various types of problems, ranging from machine learning to optimization. This paper proposes a novel hybrid model of AIS that incorporates cellular automata (CA...
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Lin Guo, Anand Balu Nellippallil, Warren F. Smith, Janet K. Allen and Farrokh Mistree
When dealing with engineering design problems, designers often encounter nonlinear and nonconvex features, multiple objectives, coupled decision making, and various levels of fidelity of sub-systems. To realize the design with limited computational resou...
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Yongyong Zhao, Jinghua Wang, Guohua Cao and Xu Yao
This study introduces a reduced-order leg dynamic model to simplify the controller design and enhance robustness. The proposed multi-loop control scheme tackles tracking control issues in legged robots, including joint angle and contact-force regulation,...
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Amin Rahimi, Seyed Mojtaba Hejazi, Mostafa Zandieh and Mirpouya Mirmozaffari
In this paper, the problem of finding an assignment of ?n? surgeries to be presented in one of ?m? identical operating rooms (ORs) or machines as the surgical case scheduling problem (SCSP) is proposed. Since ORs are among NP-hard optimization problems, ...
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Angel A. Juan, Markus Rabe, Majsa Ammouriova, Javier Panadero, David Peidro and Daniel Riera
In the field of logistics and transportation (L&T), this paper reviews the utilization of simheuristic algorithms to address NP-hard optimization problems under stochastic uncertainty. Then, the paper explores an extension of the simheuristics concep...
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