混合遗传搜索 (HGS)算法 的现代实现，专门针对有能力的车辆路径问题 (CVRP)_C++_代码_下载

[](https://github.com/vidalt/HGS-CVRP/actions/workflows/CI_Build.yml) # HGS-CVRP: A modern implementation of the Hybrid Genetic Search for the CVRP This is a modern implementation of the Hybrid Genetic Search (HGS) with Advanced Diversity Control of [1], specialized to the Capacitated Vehicle Routing Problem (CVRP). This algorithm has been designed to be transparent, specialized, and highly concise, retaining only the core elements that make this method successful. Beyond a simple reimplementation of the original algorithm, this code also includes speed-up strategies and methodological improvements learned over the past decade of research and dedicated to the CVRP. In particular, it relies on an additional neighborhood called SWAP*, which consists in exchanging two customers between different routes without an insertion in place. ## References When using this algorithm (or part of it) in derived academic studies, please refer to the following works: [1] Vidal, T., Crainic, T. G., Gendreau, M., Lahrichi, N., Rei, W. (2012). A hybrid genetic algorithm for multidepot and periodic vehicle routing problems. Operations Research, 60(3), 611-624. https://doi.org/10.1287/opre.1120.1048 (Available [HERE](https://w1.cirrelt.ca/~vidalt/papers/HGS-CIRRELT-2011.pdf) in technical report form). [2] Vidal, T. (2022). Hybrid genetic search for the CVRP: Open-source implementation and SWAP* neighborhood. Computers & Operations Research, 140, 105643. https://doi.org/10.1016/j.cor.2021.105643 (Available [HERE](https://arxiv.org/abs/2012.10384) in technical report form). We also recommend referring to the Github version of the code used, as future versions may achieve better performance as the code evolves. The version associated with the results presented in [2] is [v1.0.0](https://github.com/vidalt/HGS-CVRP/releases/tag/v1.0.0). ## Other programming languages There exist wrappers for this code in the following languages: * **C**: The **C_Interface** file contains a simple C API * **Python**: The [PyHygese](https://github.com/chkwon/PyHygese) package is maintained to interact with the latest release of this algorithm * **Julia**: The [Hygese.jl](https://github.com/chkwon/Hygese.jl) package is maintained to interact with the latest release of this algorithm We encourage you to consider using these wrappers in your different projects. Please contact me if you wish to list other wrappers and interfaces in this section. ## Scope This code has been designed to solve the "canonical" Capacitated Vehicle Routing Problem (CVRP). It can also directly handle asymmetric distances as well as duration constraints. This code version has been designed and calibrated for medium-scale instances with up to 1,000 customers. It is **not** designed in its current form to run very-large scale instances (e.g., with over 5,000 customers), as this requires additional solution strategies (e.g., decompositions and additional neighborhood limitations). If you need to solve problems outside of this algorithm's scope, do not hesitate to contact me at <thibaut.vidal@polymtl.ca>. ## Compiling the executable You need [`CMake`](https://cmake.org) to compile. Build with: ```console mkdir build cd build cmake .. -DCMAKE_BUILD_TYPE=Release make bin ``` This will generate the executable file `hgs` in the `build` directory. Test with: ```console ctest -R bin --verbose ``` ## Running the algorithm After building the executable, try an example: ```console ./hgs ../Instances/CVRP/X-n157-k13.vrp mySolution.sol -seed 1 -t 30 ``` The following options are supported: ``` Call with: ./hgs instancePath solPath [-it nbIter] [-t myCPUtime] [-bks bksPath] [-seed mySeed] [-veh nbVehicles] [-log verbose] [-it <int>] sets a maximum number of iterations without improvement. Defaults to 20,000 [-t <double>] sets a time limit in seconds. If this parameter is set, the code will be run iteratively until the time limit [-seed <int>] sets a fixed seed. Defaults to 0 [-veh <int>] sets a prescribed fleet size. Otherwise a reasonable UB on the fleet size is calculated [-round <bool>] rounding the distance to the nearest integer or not. It can be 0 (not rounding) or 1 (rounding). Defaults to 1. [-log <bool>] sets the verbose level of the algorithm log. It can be 0 or 1. Defaults to 1. Additional Arguments: [-nbGranular <int>] Granular search parameter, limits the number of moves in the RI local search. Defaults to 20 [-mu <int>] Minimum population size. Defaults to 25 [-lambda <int>] Number of solutions created before reaching the maximum population size (i.e., generation size). Defaults to 40 [-nbElite <int>] Number of elite individuals. Defaults to 5 [-nbClose <int>] Number of closest solutions/individuals considered when calculating diversity contribution. Defaults to 4 [-targetFeasible <double>] target ratio of feasible individuals in the last 100 generatied individuals. Defaults to 0.2 ``` There exist different conventions regarding distance calculations in the academic literature. The default code behavior is to apply integer rounding, as it should be done on the X instances of Uchoa et al. (2017). To change this behavior (e.g., when testing on the CMT or Golden instances), give a flag `-round 0`, when you run the executable. ## Code structure The main classes containing the logic of the algorithm are the following: * **Params**: Stores the main data structures for the method * **Individual**: Represents an individual solution in the genetic algorithm, also provides I/O functions to read and write individual solutions in CVRPLib format. * **Population**: Stores the solutions of the genetic algorithm into two different groups according to their feasibility. Also includes the functions in charge of diversity management. * **Genetic**: Contains the main procedures of the genetic algorithm as well as the crossover * **LocalSearch**: Includes the local search functions, including the SWAP* neighborhood * **Split**: Algorithms designed to decode solutions represented as giant tours into complete CVRP solutions * **CircleSector**: Small code used to represent and manage arc sectors (to efficiently restrict the SWAP* neighborhood) In addition, additional classes have been created to facilitate interfacing: * **AlgorithmParameters**: Stores the parameters of the algorithm * **CVRPLIB** Contains the instance data and functions designed to read input data as text files according to the CVRPLIB conventions * **commandline**: Reads the line of command * **main**: Main code to start the algorithm * **C_Interface**: Provides a C interface for the method ## Compiling the shared library You can also build a shared library to call the HGS-CVRP algorithm from your code. ```console mkdir build cd build cmake .. -DCMAKE_BUILD_TYPE=Release make lib ``` This will generate the library file, `libhgscvrp.so` (Linux), `libhgscvrp.dylib` (macOS), or `hgscvrp.dll` (Windows), in the `build` directory. To test calling the shared library from a C code: ```console make lib_test_c ctest -R lib --verbose ``` ## Contributing Thank you very much for your interest in this code. This code is still actively maintained and evolving. Pull requests and contributions seeking to improve the code in terms of readability, usability, and performance are welcome. Development is conducted in the `dev` branch. I recommend to contact me beforehand at <thibaut.vidal@polymtl.ca> before any major rework. As a general guideline, the goal of this code is to stay **simple**, **stand-alone**, and **spec