Applied Sciences

Material handling is an important process in open-pit mining, where trucks transport material extracted by shovels to different destinations within the mine. The decision regarding the next destination of a truck strongly influences operational efficiency. In current mining operations, this decision is typically handled by centralized dispatching systems based on predefined criteria. However, such approaches often struggle to adapt to dynamic operating conditions and rely on a central control unit, which may reduce flexibility and robustness. This paper proposes a decentralized multi-agent system for truck dispatching with reinforcement learning (MAS-TDRL). In the proposed approach, autonomous agents representing trucks, shovels, and unloading points cooperate through a negotiation mechanism based on an enhanced Contract Net Protocol to generate operational schedules. Reinforcement learning is integrated into the decision-making process of truck agents, allowing them to learn from previous negotiations and improve their participation over time. The proposed system is evaluated through simulation using scenarios based on real data from an open-pit copper mine in Chile. The results show that incorporating reinforcement learning increases the material transported per hour by approximately 18–29% compared to a multi-agent system without learning, while maintaining computation times below 10 min even in the largest scenario, which remains compatible with operational decision-making in open-pit mining contexts.

With the rapid expansion of renewable energy and the acceleration of electricity market reforms, coal-fired units are facing increasing difficulty in recovering fixed costs due to marginal cost-based bidding competition and depressed clearing prices caused by low-cost renewable integration, circumstances in which reasonable returns and investment incentives for coal-fired power plants are not guaranteed. To address this issue, this paper proposes a capacity cost compensation mechanism for coal-fired power in the electricity market environment. First, a joint clearing model for the electricity spot market considering both energy and reserve services is established, and annual market operation simulations are conducted to obtain unit output schedules, clearing prices, and annual revenues. Second, based on the long-term simulation results, the marginal clearing probability and fixed cost recovery deficit of each coal-fired unit are calculated, and a capacity compensation pricing method based on marginal clearing probability weighting is proposed to determine the system unit capacity compensation price. Subsequently, the compensated capacity is determined using the availability factor method, comprehensively reflecting each unit’s actual contribution to system capacity adequacy. Finally, case studies conducted on a modified IEEE 30-bus system validate the effectiveness of the proposed mechanism. The results demonstrate that following the implementation of the proposed mechanism, the investment payback periods of all coal-fired units are reduced to within the planned 20-year horizon, thereby ensuring the sustainable operation of coal-fired units and maintaining adequate reliability margins in the power system.

Over the past two decades, Olympic swimming performance has improved. However, less attention has been given to the evolution of Olympic Qualification Time (OQT) standards. This retrospective observational study analyzed event-specific qualification standards for all male pool swimming events. Data were extracted from publicly available documents and competition reports. Descriptive statistics, percentage change calculations, Pearson correlation analysis, and paired-sample t-tests between Olympic cycles from 2008 to 2028 were performed. For 2028, the OQTs were defined as the 14th fastest entry time from the 2024 Olympic Games. Across all events, the mean cumulative reduction in OQTs between Beijing 2008 and Los Angeles 2028 was 2.86 ± 0.54%, corresponding to an average proportional decrease of 0.6% per Olympic cycle, with trend analysis confirming statistical significance (p < 0.001). Event-level analysis revealed the greatest tightening in the 100 m breaststroke (−3.74%) and 100 m butterfly (−3.25%). When grouped by distance, sprint events (50–100 m) showed the strongest overall tightening (−3.57%), followed by middle-distance (200–400 m, −2.08%) and long-distance (800–1500 m, −2.45%). When grouped by stroke, butterfly (−3.28%) and freestyle (−3.20%) showed the largest decrease, whereas individual medley (−2.29%) demonstrated the smallest decrease. A strong positive correlation was observed between OQT tightening and Olympic performance improvement across events (r = 0.74). These findings indicate that OQTs have become demanding and broadly aligned with elite performance progression, providing applied benchmarks for coaches and performance staff.