Cellular robotic system with stationary robots and its application to manufacturing lattices

Wang, J.; Beni, G.

doi:10.1109/isic.1989.238706

Cited by 13 publications

(6 citation statements)

References 4 publications

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“…The official website 4 of the ITC2021 overviews the problem instances and specifications that are available in 4 groups showing the number of teams, slots, and constraints classification for each instance.…”

Section: Methodsmentioning

confidence: 99%

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An Enhanced Particle Swarm Optimization for ITC2021 Sports Timetabling

Alsmadi¹,

Jaradat²,

Alzaqebah³

et al. 2022

Computers, Materials &Amp; Continua

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Timetabling problem is among the most difficult operational tasks and is an important step in raising industrial productivity, capability, and capacity. Such tasks are usually tackled using metaheuristics techniques that provide an intelligent way of suggesting solutions or decision-making. Swarm intelligence techniques including Particle Swarm Optimization (PSO) have proved to be effective examples. Different recent experiments showed that the PSO algorithm is reliable for timetabling in many applications such as educational and personnel timetabling, machine scheduling, etc. However, having an optimal solution is extremely challenging but having a sub-optimal solution using heuristics or metaheuristics is guaranteed. This research paper seeks the enhancement of the PSO algorithm for an efficient timetabling task. This algorithm aims at generating a feasible timetable within a reasonable time. This enhanced version is a hybrid dynamic adaptive PSO algorithm that is tested on a round-robin tournament known as ITC2021 which is dedicated to sports timetabling. The competition includes several soft and hard constraints to be satisfied in order to build a feasible or sub-optimal timetable. It consists of three categories of complexities, namely early, test, and middle instances. Results showed that the proposed dynamic adaptive PSO has obtained feasible timetables for almost all of the instances. The feasibility is measured by minimizing the violation of hard constraints to zero. The performance of the dynamic adaptive PSO is evaluated by the consumed computational time to produce a solution of feasible timetable, consistency, and robustness. The dynamic adaptive PSO showed a robust and consistent performance in producing a diversity of timetables in a reasonable computational time.

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Section: Methodsmentioning

confidence: 99%

“…It comprises a collective behavior of natural or artificial self-organized and decentralized systems [3]. It was first introduced by [4], in the field of cellular robotic systems. Swarm intelligence systems comprise an agent's population of locally interacting with each other and with their environment.…”

mentioning

confidence: 99%

An Enhanced Particle Swarm Optimization for ITC2021 Sports Timetabling

Alsmadi¹,

Jaradat²,

Alzaqebah³

et al. 2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Swarm Intelligence (SI) was introduced by (Wang & Beni 1989) for simple cellular robotic systems. SI is an intelligent multiagent system that simulates the behaviour of social insects such as ants, bees, termites and cockroaches and also swarms such as a flock of birds, a school of fishes, and a herd of quadrupeds.…”

Section: Swarm Intelligencementioning

confidence: 99%

A state-of-the-Art review of heuristic and metaheuristic optimization techniques for the management of water resources

Kumar

Yadav

2022

Water Supply

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Water resource management is a complex engineering problem, due to the stochastic nature of inflow, various demands and environmental flow downstream. With the increase in water consumption for domestic use and irrigation, it becomes more challenging. Many more difficulties, such as non-convex, nonlinear, multi-objective, and discontinuous functions, exist in real-life. From the past two decades, heuristic and metaheuristic optimization techniques have played a significant role in managing and providing better performance solutions. The popularity of heuristic and metaheuristic optimization techniques has increased among researchers due to their numerous benefits and possibilities. Researchers are attempting to develop more accurate and efficient models by incorporating novel methods and hybridizing existing ones. This paper's main contribution is to show the state-of-the-art of heuristic and metaheuristic optimization techniques in water resource management. The research provides a comprehensive overview of the various techniques within the context of a thorough evaluation and discussion. As a result, for water resource management problems, this study introduces the most promising evolutionary and swarm intelligence techniques. Hybridization, modifications, and algorithm variants are reported to be the most successful for improving optimization techniques. This survey can be used to aid hydrologists and scientists in deciding the proper optimization techniques.

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“…Among them, swarm intelligence methods such as an ACO (Ant Colony) and PSO are well‐known techniques that were employed in this work on artificial intelligence. The expression was introduced by Wang and Beni in 1989, 49 in the context of cellular robotic systems. PSO is a robust stochastic optimization technique based on the movement and intelligence of swarms.…”

Section: Theorymentioning

confidence: 99%

Optimization of reaction parameters of Fischer–Tropsch synthesis in the presence of Co‐V/Al₂O₃ nano‐catalyst

Hafizi

Koolivand‐Salooki²,

Esfandyari

et al. 2022

Int J of Chemical Kinetics

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Nano-catalyst of cobalt-vanadate (Co-V/Al 2 O 3 , supported on alumina) application in Fischer-Tropsch process (FT) was explored in a various conversions of synthesis gas. The catalyst characterization was performed using different methods including Brunauer-Emmett-Teller (BET) surface area, X-ray fluorescence (XRF), X-ray diffraction (XRD), Temperature programmed reduction (TPR) profile, and Transmission electron microscopy (TEM). Due to the extreme complexity and nonlinearity of catalytic processes, adaptive network based fuzzy interface system (ANFIS) was developed as a predictive tool for evaluation of Co-V/Al 2 O 3 nano-catalyst performance in FT process. Input vector included reaction condition such as, pressure, temperature, time, and CO/H 2 ratio of different experiments while the outputs were composition of CO, CO 2 , and CH 4 . The proposed model was used for optimization of the process, also the optimal operating conditions were acquired using particle swarm optimization (PSO). The performance of the algorithms and the quality of the solutions were measured by introducing the optimal operating conditions to obtained model. Comparative studies and results analysis were then conducted on the optimization results. The model result shows a good consistency with experimental observations.

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Cellular robotic system with stationary robots and its application to manufacturing lattices

Cited by 13 publications

References 4 publications

An Enhanced Particle Swarm Optimization for ITC2021 Sports Timetabling

An Enhanced Particle Swarm Optimization for ITC2021 Sports Timetabling

A state-of-the-Art review of heuristic and metaheuristic optimization techniques for the management of water resources

Optimization of reaction parameters of Fischer–Tropsch synthesis in the presence of Co‐V/Al₂O₃ nano‐catalyst

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Cellular robotic system with stationary robots and its application to manufacturing lattices

Cited by 13 publications

References 4 publications

An Enhanced Particle Swarm Optimization for ITC2021 Sports Timetabling

An Enhanced Particle Swarm Optimization for ITC2021 Sports Timetabling

A state-of-the-Art review of heuristic and metaheuristic optimization techniques for the management of water resources

Optimization of reaction parameters of Fischer–Tropsch synthesis in the presence of Co‐V/Al2O3 nano‐catalyst

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Product

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Optimization of reaction parameters of Fischer–Tropsch synthesis in the presence of Co‐V/Al₂O₃ nano‐catalyst