Simulation Budget Allocation for Further Enhancing theEfficiency of Ordinal Optimization
Discrete Event Dynamic Systems
Dynamic Control of Logistics Queueing Networks for Large-Scale Fleet Management
Transportation Science
An Adaptive Dynamic Programming Algorithm for the Heterogeneous Resource Allocation Problem
Transportation Science
Solving a Practical Pickup and Delivery Problem
Transportation Science
Vehicle Routing and Scheduling with Full Truckloads
Transportation Science
Efficient Insertion Heuristics for Vehicle Routing and Scheduling Problems
Transportation Science
An Exact Algorithm for the Multiple Vehicle Pickup and Delivery Problem
Transportation Science
Stochastic Simulation Optimization: An Optimal Computing Budget Allocation
Stochastic Simulation Optimization: An Optimal Computing Budget Allocation
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The local pickup and delivery problem (LPDP) is an essential operational problem in intermodal industry. While the problem with deterministic settings is already difficult to solve, in reality, there exist a set of loads, called uncertain loads, which are unknown at the beginning of the day. But customers may call in during the day to materialize these loads. In this paper, we call the LPDP considering these uncertain loads as the stochastic LPDP. The problem description and the mathematical modeling of stochastic LPDP are discussed. Then, a simulation-based optimization approach is proposed to solve the problem, which features in a fast solution generation procedure and an intelligent simulation budget allocation framework. The numerical examples show the best strategy to consider the stochastic loads in the planning process and validate the benefits compared to its deterministic counterpart.