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Hu Lab
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The lab does research on combinatorial optimization, aiming to develop practical approximation methods.
AboutAbout the lab
Finding reasonably accurate approximate solutions in realistic time.
Hu Lab studies the development of practical approximation methods for combinatorial optimization problems such as placement problems, vehicle routing problems, and scheduling problems.
Combinatorial optimization problems are problems in which the space where solutions are defined and the constraints are discrete. Many of the problems that arise in society can be expressed in this form.
In many cases, obtaining an optimal solution within a realistic computation time is extremely difficult.
For this reason, methods that efficiently find approximate solutions of moderate accuracy are considered useful.
The research page mainly introduces research the lab has done so far, and its list of publications is recorded only up to around 2019.
Key terms
- Combinatorial optimization problem
- A problem in which the space where solutions are defined and the constraints are discrete. The goal is to find the best solution among them
- Approximate solution
- A solution that is not necessarily optimal, but can be obtained with moderate accuracy within a realistic computation time
- Local search
- A search method that repeatedly improves the current solution by making small changes to it. It can be implemented once an evaluation of solutions and a definition of the neighborhood are given
ResearchResearch themes
The lab aims to develop practical approximation methods for combinatorial optimization problems, and has worked on placement problems, vehicle routing problems, and scheduling problems. In real-world problems, an approximate solution of moderate accuracy is considered sufficiently practical, and the lab works on methods that find such approximate solutions efficiently.
*Illustrative imageShape Placement Problems
This theme deals with the problem of efficiently placing products in a space under various constraints. According to the lab, approximating general shapes with bitmap shapes makes overlap detection easy, which makes it possible to design fast, high-performing algorithms.
*Illustrative imageVehicle Routing Problems
This is the problem of finding the minimum-cost set of routes by which multiple vehicles visit multiple customers. One promising approach is local search, and the lab holds that achieving high performance requires neighborhood search with carefully designed data structures and the like.
*Illustrative imageScheduling Problems and Column Generation
For the airline crew scheduling problem, the lab proposed a solution method that uses a column generation approach based on the set covering problem. The method maintains a set of promising flight sequences and repeatedly performs operations that generate new flight sequences.
MembersFaculty
- Hu Hu
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Pantos Logistics - Warehouse picture” Romlogistics / CC BY-SA 3.0 (cropped)
- Shape Placement Problems: “Tetrahedron packing structure png” Eigenbra / CC BY-SA 4.0 (cropped)
- Vehicle Routing Problems: “StrongPak Navistar Utilimaster delivery truck” MobiusDaXter / CC BY-SA 3.0 (cropped)
- Scheduling Problems and Column Generation: “Biltmore Room schedule board and clock, Grand Central Terminal” TheCatalyst31 / CC BY-SA 4.0 (cropped)
- Related lab (松崎研究室): “A medical dictionary for nurses (1914)” Pope, Amy Elizabeth / Public domain (cropped)
- Related lab (鍋島研究室): “EFTA00001987 - Blackboard filled with chalk drawings and equations including a face sketch and diagrams sits in a room with ornate columns and sculptures” Federal Bureau of Investigation / Public domain (cropped)
- Related lab (柳田研究室): “Entropy flip 2 coins” http://www.cngcoins.com/ / CC BY-SA 3.0 (cropped)
- Related lab (犬伏研究室): “Turbulence arbre 2 modifié-1” Lamiot / CC BY-SA 3.0 (cropped)
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