A5103097246- Scheduling and Optimization Algorithms
- Advanced Manufacturing and Logistics Optimization
- AI-based Problem Solving and Planning
- Constraint Satisfaction and Optimization
- Optimization and Packing Problems
- Assembly Line Balancing Optimization
- Optimization and Search Problems
- Enzyme Catalysis and Immobilization
- Nicotinic Acetylcholine Receptors Study
- Microbial Metabolic Engineering and Bioproduction
- Metaheuristic Optimization Algorithms Research
- Urban and Freight Transport Logistics
- Distributed and Parallel Computing Systems
- Vehicle Routing Optimization Methods
- Electrochemical sensors and biosensors
- Logic, Reasoning, and Knowledge
- Nonlinear Optical Materials Studies
- Biofuel production and bioconversion
- Water-Energy-Food Nexus Studies
- Porphyrin and Phthalocyanine Chemistry
- Cognitive Computing and Networks
- Pharmacological Receptor Mechanisms and Effects
- Satellite Communication Systems
- Phytochemical compounds biological activities
- Air Quality and Health Impacts
Nanjing Forestry University
2022-2025
Institute of Chemical Industry of Forest Products
2022-2025
Kunming University of Science and Technology
2025
Beijing Institute of Technology
2012-2024
Hohai University
2015-2024
Yangzhou University
2024
Changchun University of Technology
2022-2024
Nanjing University of Posts and Telecommunications
2023
Anyang Institute of Technology
2023
Wenzhou University
2023
Reducing energy costs has become an important concern for sustainable manufacturing systems, owing to the environment. We present a multi-objective hybrid ant colony optimisation (MHACO) algorithm real-world two-stage blocking permutation flow shop scheduling problem address trade-off between total (TEC) and makespan (Cmax) as measures of service level with time-of-use (TOU) electricity price. explore energy-saving potential industry in consideration differential generated by variable-speed...
A proportional-derivative (PD)-type iterative learning control (ILC) combined with fault-tolerant (FTC) for a discrete-time batch process time-varying delays and uncertainties is presented in this paper. The main goals of paper are to drive the considered output profile desired reference avoidance possible faults, uncertainties. First, nonlinear estimation problem simplified linear one by introducing an appropriate system reparametrisation deal simultaneous state fault. Second, solve...
AbstractBatch processing machines (BPMs) have important applications in a variety of industrial systems. This paper considers the problem scheduling two BPMs flow shop with arbitrary release times and blocking such that makespan is minimised. The formulated as mixed integer programming model. Subsequently, hybrid discrete differential evolution (HDDE) algorithm proposed. In algorithm, individuals population are first represented job sequences, mutation crossover operators applied based on...
Batch scheduling is a prevalent policy in many industries such as burn-in operations semiconductor manufacturing and heat treatment metalworking. In this paper, we consider the problem of minimising makespan on single batch processing machine presence dynamic job arrivals non-identical sizes. The under study NP-hard. Consequently, develop number efficient construction heuristics. performance proposed heuristics evaluated by comparing their results to two lower bounds, other solution...
AbstractNeuronal nicotinic acetylcholine receptors (nAChRs) belong to a superfamily of ligand-gated ion channel and are distributed extensively throughout the central peripheral nervous systems. The structural functional diversity these has stimulated interest in development subtype-selective agonists, as result greater understanding role neuropathology disease, including Alzheimer’s Parkinson’s Tourette’s syndrome, drug addiction pain. Surprisingly, much less attention been focused on...
Purpose Abundant studies of outpatient visits apply traditional recurrent neural network (RNN) approaches; more recent methods, such as the deep long short-term memory (DLSTM) model, have yet to be implemented in efforts forecast key hospital data. Therefore, current study aims reports on an application DLSTM model multiple streams healthcare Design/methodology/approach As most advanced machine learning (ML) method, static and dynamic models aim time-series data, daily patient visits. With a...
This work reports on the exceptional optical limiting performance of a novel D–A-type compound, namely, LaPc-4(C60), wherein lanthanide phthalocyanine is used as donor and four C60 are acceptors. In addition, phenyl ether bonds were introduced into molecule, making it semirigid increasing its solubility. At same time, bond could act π-electron bridge, which increases electron transfer pathway, expands π-conjugated system, reduces spatial site resistance molecule. Furthermore, uniform...
Multi Automated Guided Vehicle (multi-AGV) systems are widely used in Work-in-Process (WIP) warehouses to improve the efficiency of material transportation. However, collisions and deadlocks between AGVs inevitable. Many algorithms have been proposed solve these problems, but their performance is inefficient WIP warehouse due lack consideration its features. In this paper, fill gap current research real-world application requirement, we construct a collision deadlock solving model for...
Let Y be a random variable whose moment generating function exists in neighborhood of the origin. In this paper, we study probabilistic central Bell polynomials associated with Y, as extension polynomials. addition, investigate factorial numbers second kind and Fubini Y. The aim paper is to derive some properties, explicit expressions, certain identities recurrence relations for those numbers.
An accurate prediction model for dam deformation is crucial ensuring the safety and operational integrity of structures. This study introduces a hybrid modeling approach that integrates long short-term memory (LSTM) networks with Kolmogorov–Arnold (KANs). Additionally, incorporates dual-stage attention mechanism (DA) includes both factor temporal components, enhancing model’s precision interpretability. The effectiveness DA-LSTM-KAN was validated through case involving concrete gravity dam....