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Titlebook: Operations Research and Enterprise Systems; 11th International C Federico Liberatore,Slawo Wesolkowski,Greg H. Parl Conference proceedings

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楼主: 弄混
发表于 2025-3-28 17:32:48 | 显示全部楼层
An Urban-Scale Application of the Problem of Designing Green Tourist Trips with Time Windows of three different objectives: 1) the minimization of transportation costs and expense incurred to access the tourist sites to be visited; 2) the minimization of . emissions generated by the vehicles used for travel; and 3) the maximization of the attractiveness of the tourist sites to be visited,
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Customer Satisfaction and Company Revenue: A Solution Approach for the Passenger Management on Busesgy, and a model solution in a context of perfect knowledge of the occurred demand. The computational results show that the booking limit policy performs better than the first came first served strategy and in many cases equals the performance of the perfect knowledge strategy.
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Reinforcement Learning Algorithms: Categorization and Structural Propertiesct-fit algorithms for their specific problems. In this paper, we identify and explain essential properties of RL problems and algorithms. Our discussion of these concepts can be used to select, optimize, and compare RL algorithms and their extensions with respect to particular problems, as well as reason about their performance.
发表于 2025-3-29 16:56:35 | 显示全部楼层
Optimization of the Storage Location Assignment Problem Using Nested Annealing methods improve performance, with total travel-cost reductions of up to 30% within 8 h of CPU-time. We share a public repository with SLAP instances and corresponding benchmark results on the generalizable TSPLIB format.
发表于 2025-3-29 23:17:13 | 显示全部楼层
Robust Optimization for Operating Room Scheduling with Uncertain Surgical Durations: Impact of Risk-a solution faster than stochastic programming. In specific control conservative, robust optimization exhibits the same performance as stochastic programming. The robust optimization model is more effective for operating room managers who desire to obtain an accurate solution quickly.
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Multiple Heuristics with Reinforcement Learning to Solve the Safe Shortest Path Problem in a Warehouducing a time-dependent estimation of the risk induced by the traversal of an arc at a given time. We propose a model and design a bi-level heuristic with dynamic programming and an A*-like heuristic along with three methods to generate speed functions which can all rely on a reinforcement learning scheme to route and schedule this vehicle.
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