Team Unagi's repository for ICFPC 2019

Brief directions for judges to build/run the solution

Requirements

• Rust 1.35.0

Solving tasks

cd wata
cargo run --release task.desc "" > task.sol    # Buying nothing
cargo run --release task.desc "CC" > task.sol  # Buying CC

Solving puzzles

cd puzzle
cargo run task.cond task.desc

Deciding what to buy

cd knapsack
cargo run --bin main knapsack-in.txt 748091 > knapsack-out.txt

Each line of knapsack-in.txt should contain problem ID, buy string, solution ID, and time, which are separated by commas. For example:

prob-002,,29259,381
prob-002,B,50721,356
prob-002,C,59200,224
prob-002,CB,51232,226
prob-003,,34881,210
prob-003,B,52255,210
prob-003,C,47656,128
prob-003,CB,52766,128
...

It outputs selected solutions to be submitted to stdout.

Description of the solution approach

Solving tasks

• A single-worker solution is constructed by the left-hand rule (https://en.wikipedia.org/wiki/Maze_solving_algorithm#Wall_follower). See chokudai/src/lib.rs.
• An initial sequence is prepared, which collects boosters and replicates workers. It uses greedy algorithms and dynamic programming. See common/src/{bootstrap.rs, bootstrap_clone.rs}.
• Given them, multi-worker solution is created by splitting the single-worker solution and concatenating to the initial sequence. See wata/src/main.rs.
• Local refinement is applied to the solution. It tries to improve the solution by removing some parts of the solution and reconstructing actions to perform the same things with shorter steps. It uses depth-first and breadth-first searches. See common/src/local_optimization.rs.

Solving puzzles

• Our puzzle solvers heavily relies on narrow paths for satisfying point constraints.
• It then adjusts the area and number of vertices to satisfy the area and vertices constraings.
• See puzzle/src/*.rs.

Deciding what to buy

• We first prepare solutions for different buy settings for each task. Then, we need to select what to buy for all tasks. We formalized this problem as a variant of knapsack problems, and solved it by using dynamic programming (https://en.wikipedia.org/wiki/Knapsack_problem#Dynamic_programming_in-advance_algorithm). See knapsack/src/*.rs.

Feedback about the contest

• The conditions of mining puzzles seem too loose, even at last rounds. Top teams could solve all mining puzzles and performance of puzzle solvers did not matter. In additoin, there was little incentive to create interesting and/or hard tasks for mining puzzles.

Self-nomination for judges’ prize

Our mining puzzle solver creates beautiful tasks. Please see 83.png. It illustrates our task that is officially selected for block 83.