239 citations · 256 across the 9 of their papers we have counts for
11 papers
In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization
Tingyang Wei, Haofeng Wu, Jiao Liu +3
Multi-task optimization (MTO) addresses a set of optimization tasks simultaneously, often suffering from inaccurate inter-task relationship estimation under limited evaluation budg…
Amortized Multi-Objective Optimization Across Tasks with Generative Solution Modeling
Tingyang Wei, Jiao Liu, Abhishek Gupta +3
Many real-world applications require solving families of expensive multi-objective optimization problems~(EMOPs) under varying operational conditions. This can be formulated as par…
()-Parametric Multi-Task Optimization: Joint Search in Solution and Infinite Task Spaces
Tingyang Wei, Jiao Liu, Abhishek Gupta +2
Multi-task optimization is typically characterized by a fixed and finite set of tasks. The present paper relaxes this condition by considering a non-fixed and potentially infinite…
Identifying the Key Attributes in an Unlabeled Event Log for Automated Process Discovery
Kentaroh Toyoda, Rachel Gan Kai Ying, Allan NengSheng Zhang +1
Process mining discovers and analyzes a process model from historical event logs. The prior art methods use the key attributes of case-id, activity, and timestamp hidden in an even…
Learning to Solve Multiple-TSP with Time Window and Rejections via Deep Reinforcement Learning
Rongkai Zhang, Cong Zhang, Zhiguang Cao +5
We propose a manager-worker framework based on deep reinforcement learning to tackle a hard yet nontrivial variant of Travelling Salesman Problem (TSP), \ie~multiple-vehicle TSP wi…
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
Cong Zhang, Wen Song, Zhiguang Cao +3
Priority dispatching rule (PDR) is widely used for solving real-world Job-shop scheduling problem (JSSP). However, the design of effective PDRs is a tedious task, requiring a myria…
Shipper Cooperation in Stochastic Drone Delivery: A Dynamic Bayesian Game Approach
Suttinee Sawadsitang, Dusit Niyato, Tan Puay Siew +2
With the recent technological innovation, unmanned aerial vehicles, known as drones, have found numerous applications including package and parcel delivery for shippers. Drone deli…
Re-route Package Pickup and Delivery Planning with Random Demands
Suttinee Sawadsitang, Dusit Niyato, Kongrath Suankaewmanee +1
Recently, a higher competition in logistics business introduces new challenges to the vehicle routing problem (VRP). Re-route planning, also known as dynamic VRP, is one of the imp…
Multi-Objective Optimization for Drone Delivery
Suttinee Sawadsitang, Dusit Niyato, Puay Siew Tan +1
Recently, an unmanned aerial vehicle (UAV), as known as drone, has become an alternative means of package delivery. Although the drone delivery scheduling has been studied in recen…
Joint Ground and Aerial Package Delivery Services: A Stochastic Optimization Approach
Suttinee Sawadsitang, Dusit Niyato, Puay-Siew Tan +1
Unmanned aerial vehicles (UAVs), also known as drones, have emerged as a promising mode of fast, energy-efficient, and cost-effective package delivery. A considerable number of wor…
Supplier Cooperation in Drone Delivery
Suttinee Sawadsitang, Dusit Niyato, Tan Puay Siew +1
Recently, unmanned aerial vehicles (UAVs), also known as drones, has emerged as an efficient and cost-effective solution for package delivery. Especially, drones are expected to in…