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Optimal scheduling of battery energy storage train and renewable power generation
With the increasing penetration of renewable energy sources (RES), a battery energy storage (BES) Train supply system with flexibility and high...
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Train maintenance personnel shift scheduling: case study
In this study, the shift scheduling problem of the personnel who maintain the 324 trains operating on the lines of the Ankara Metro, which carry...
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Goal programming models for high-speed train crew scheduling problem
High freight and passenger-carrying capacity, providing a fast and safe journey, and its tourism potential, railway transportation remains preferable...
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Stability assessment of railway trackwork scheduling in Sweden
Ensuring the reliability of railway transportation is heavily dependent on the quality of its infrastructure. In this regard, renewal and maintenance...
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Economical Speed for Optimizing the Travel Time and Energy Consumption in Train Scheduling using a Fuzzy Multi-Objective Model
Speed is one of the most influential variables in both energy consumption and train scheduling problems. Increasing speed guarantees punctuality,...
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Train Length and Service Frequency Optimization: Passenger Health Expense Perspective
The urban transport rail network is represented by operational lines and associated variables such as the origin/destination matrix, ridership, and...
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Collaborative Optimization of Train Scheduling and Passenger Flow Control with Adjustable Dwell Time on a Congested Metro Line
Metro lines in megacities often experience extreme congestion during peak hours, causing passengers to strand on platforms and pose serious...
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Energy-Efficient Train Timetabling
Running time calculation is an essential ingredient in train timetabling. Traditionally, the technical minimum running times are computed in detail...
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Review evolution of dual-resource-constrained scheduling problems in manufacturing systems: modeling and scheduling methods’ trends
Dual-resource-constrained scheduling problems (DRCSP) have been hotly debated during the last two decades. DRCSPs focus on the causes and...
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Digital twin-enabled adaptive scheduling strategy based on deep reinforcement learning
The modern complicated manufacturing industry and smart manufacturing tendency have imposed new requirements on the scheduling method, such as...
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Smart scheduling of hanging workshop via digital twin and deep reinforcement learning
The complexity of job-shop environments poses significant challenges for effective scheduling in the manufacturing industry. Flexible job-shop...
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Density-based anti-clustering for scheduling D2D communications
Wireless link scheduling in device-to-device (D2D) networks is an NP-hard problem. As a solution, multiple supervised deep learning (DL) models have...
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Adaptive Multi-category Train Scheduling Validation Based on Fatigue Reliability of a Long-Span Suspension Bridge
Fatigue is an important issue in the durability of long-span cable-supported bridges. These structures are submitted repetitively to loads such as...
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Assembly line balancing and optimal scheduling for flexible manufacturing workshop
In order to adapt to the changing and personalized market demand, the traditional single-type mass production manufacturing mode is gradually...
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Integrated optimization of train services plan and passenger flow control on an oversaturated suburban metro line
Suburban metro lines play an important role in daily commuting, which transport passengers from suburban areas to the city center in the morning...
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A Review on Intelligent Scheduling and Optimization for Flexible Job Shop
Flexible job shop scheduling problem is a NP-hard combinatorial optimization problem, which has significant applications in the field of workshop...
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Autonomous imaging scheduling networks of small celestial bodies flyby based on deep reinforcement learning
During the flyby mission of small celestial bodies in deep space, it is hard for spacecraft to take photos at proper positions only rely on...
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The shunting scheduling of EMU first-level maintenance in a stub-end depot
While solving the shunting scheduling of EMU first-level maintenance (SSEFM), most existing literature assumed a single maintenance route for all...
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Pattern learning for scheduling microservice workflow to cloud containers
Patterns are crucial for efficiently scheduling microservice workflow applications to containers in cloud computing scenarios. However, it is...
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A combined priority scheduling method for distributed machine learning
Algorithms and frameworks for distributed machine learning have been widely used in numerous artificial intelligence engineering applications. A...
