AGV_quantum

Scripts

In directory examples there are AGVs scheduling problems. In order of increasing size of the problem these are:

• example_tiny.py - 2 AGVs reduced size
• example_smallest.py - 2 AGVs, 4 zones
• example_small.py - 4 AGVs, 4 zones
• example_medium_small.py - 6 AGVs, 7 zones
• example_medium.py - 7 AGVs, 7 zones
• example_large.py - 12 AGVs, 7 zones
• example_largest.py - 15 AGVs, 7 zones

Usage

To run this project in terminal use path/to/project> python -m run_examples

There are optional boolean parameters (1 yes, 0 no):

• --solve_linear - if 1 solve ILP on CPLEX, if 0 solve on hybrid quantum classical
• --hyb_solver chose particular hybrid solver "bqm" or "cqm" are supported, for "bqm" penalty parameter can be set in the script (works if --solve_linear = 0),
• --train_diagram - plot "train diagram" for given problem (works if --solve_linear = 1).

Examples:

python -m run_examples --solve_linear 1 --train_diagram 1 --example "small"

python -m run_examples --solve_linear 0 --example "small" --hyb_solver "bqm"

following examples are supported: "tiny", "smallest", "small", "medium_small", "medium", "large", "largest"

Tho check solutions use:

python -m check_sol --example "small" --hyb_solver "cqm"

To run tests use path/to/project> python3 -m unittest

Computational results

In folder annealing_results there are results on quantum and hybrid devices.

In folder lp_files there are saved linear models for checkout of quantum solver.

Citing this work

The code was partially supported by:

• Foundation for Polish Science (FNP) under grant number TEAM NET POIR.04.04.00-00-17C1/18-00
• National Science Centre, Poland under grant number 2022/47/B/ST6/02380, and under grant number 2020/38/E/ST3/00269