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Move subset_sum and multiple_choice_subset_sum to another repo
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‎.github/workflows/build.yml‎

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python-version: ["3.8"]
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env:
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KNAPSACK_DATA: ${{ github.workspace }}/data/knapsack
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SUBSET_SUM_DATA: ${{ github.workspace }}/data/subset_sum
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MULITPLE_CHOICE_SUBSET_SUM_DATA: ${{ github.workspace }}/data/multiple_choice_subset_sum
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KNAPSACK_DATA: ${{ github.workspace }}/data
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steps:
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- name: Checkout code
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python-version: ${{ matrix.python-version }}
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- name: Download data
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run: |
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python3 -m pip install gdown
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python3 -m pip install -r requirements.txt
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python3 -u scripts/download_data.py
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- name: Build
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run: |
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cmake -S . -B build -DCMAKE_BUILD_TYPE=Release
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cmake --build build --config Release --parallel
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cmake --install build --config Release --prefix install
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- name: Run unit tests
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working-directory: build/test
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run: ctest --parallel
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run: ctest --test-dir build/test --parallel
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- name: Run tests
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run: python3 -u scripts/run_tests.py test_results
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- name: Checkout main branch

‎README.md‎

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# KnapsackSolver
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A solver for some knapsack problems:
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* 0-1 knapsack problem
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* Subset sum problem
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* Multiple-choice subset sum problem
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A solver for the 0-1 knapsack problem
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![knapsack](knapsack.png?raw=true "knapsack")
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[image source](https://commons.wikimedia.org/wiki/File:Knapsack.svg)
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These problems often appear as subproblems of more complex problems. For example:
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* To generate cuts in branch-and-cut algorithms
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* To solve pricing problems in column generation algorithms
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* To lift bin and item dimensions in packing problems
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And therefore, having efficient algorithms with reliable implementations to solve them is very useful.
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The goal of this repository is to provide such efficient and reliable implementations.
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Here are some usage examples of this library:
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* [Lifting the length of a bin in a 3D packing problem](https://github.com/fontanf/packingsolver/blob/2cddb90686fb4a0e92f4ee1b4335ceaa2048d2f4/src/boxstacks/branching_scheme.cpp#L272)
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* [Solving a 0-1 knapsack subproblem inside an algorithm for a geometrical variable-sized bin packing problem](https://github.com/fontanf/packingsolver/blob/2cddb90686fb4a0e92f4ee1b4335ceaa2048d2f4/src/algorithms/dichotomic_search.hpp#L149)
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* Solving the pricing problem inside a column generation algorithm for the [cutting stock problem](https://github.com/fontanf/columngenerationsolver/blob/096802d9e20d2826aed5b44e3b68ac9df6b20da2/include/columngenerationsolver/examples/cutting_stock.hpp#L123), the [multiple knapsack problem](https://github.com/fontanf/columngenerationsolver/blob/096802d9e20d2826aed5b44e3b68ac9df6b20da2/include/columngenerationsolver/examples/multiple_knapsack.hpp#L154), or the [genralized assignment problem](https://github.com/fontanf/generalizedassignmentsolver/blob/68be0ab77efd897fd583f1031dd6cbc946b33f5a/src/algorithms/column_generation.cpp#L177)
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* [Solving a 0-1 knapsack subproblem inside an algorithm for the packing while travelling problem](https://github.com/fontanf/travellingthiefsolver/blob/ce1b6805e8aee8ee3300fbbc97dbc9153eecff01/src/packing_while_travelling/algorithms/sequential_value_correction.cpp#L19)
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<!--Here are some usage examples of this library:-->
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<!--* [Solving a 0-1 knapsack subproblem inside an algorithm for a geometrical variable-sized bin packing problem](https://github.com/fontanf/packingsolver/blob/2cddb90686fb4a0e92f4ee1b4335ceaa2048d2f4/src/algorithms/dichotomic_search.hpp#L149)-->
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<!--* Solving the pricing problem inside a column generation algorithm for the [cutting stock problem](https://github.com/fontanf/columngenerationsolver/blob/096802d9e20d2826aed5b44e3b68ac9df6b20da2/include/columngenerationsolver/examples/cutting_stock.hpp#L123), the [multiple knapsack problem](https://github.com/fontanf/columngenerationsolver/blob/096802d9e20d2826aed5b44e3b68ac9df6b20da2/include/columngenerationsolver/examples/multiple_knapsack.hpp#L154), or the [genralized assignment problem](https://github.com/fontanf/generalizedassignmentsolver/blob/68be0ab77efd897fd583f1031dd6cbc946b33f5a/src/algorithms/column_generation.cpp#L177)-->
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<!--* [Solving a 0-1 knapsack subproblem inside an algorithm for the packing while travelling problem](https://github.com/fontanf/travellingthiefsolver/blob/ce1b6805e8aee8ee3300fbbc97dbc9153eecff01/src/packing_while_travelling/algorithms/sequential_value_correction.cpp#L19)-->
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## Implemented algorithms
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### Knapsack
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* Greedy
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* `O(n)` `-a greedy`
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* Primal-dual (minknap)
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* List (partial solution) `-a "dynamic-programming-primal-dual --partial-solution-size 64 --pairing 0"`
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### Subset sum
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* Dynamic programming
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* Bellman
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* Array `-a dynamic-programming-bellman-array`
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* List (only optimal value) `-a dynamic-programming-bellman-list`
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* Word RAM (only optimal value) `-a dynamic-programming-bellman-word-ram`
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* Word RAM with recursive scheme `-a dynamic-programming-bellman-word-ram-rec`
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* Balancing
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* Array (only optimal value) `-a dynamic-programming-balancing-array`
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### Multiple-choice subset sum
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* Dynamic programming
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* Bellman
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* Array `-a dynamic-programming-bellman-array`
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* Word RAM (only optimal value) `-a dynamic-programming-bellman-word-ram`
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* Word RAM with recursive scheme `-a dynamic-programming-bellman-word-ram-rec`
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## Usage
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### Command line
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Solve:
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```shell
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./install/bin/knapsacksolver_knapsack --verbosity-level 1 --algorithm dynamic-programming-primal-dual --input data/knapsack/largecoeff/knapPI_2_10000_10000000/knapPI_2_10000_10000000_50.csv --format pisinger
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./install/bin/knapsacksolver --verbosity-level 1 --algorithm dynamic-programming-primal-dual --input data/knapsack/largecoeff/knapPI_2_10000_10000000/knapPI_2_10000_10000000_50.csv --format pisinger
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```
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```
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====================================
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KnapsackSolver
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====================================
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Problem
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-------
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Knapsack problem
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Instance
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--------
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Number of items: 10000
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Feasible: 1
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```
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```shell
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./install/bin/knapsacksolver_subset_sum --verbosity-level 1 --input data/subset_sum/pthree/pthree_1000_1 --algorithm dynamic-programming-bellman-word-ram-rec
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```
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```
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====================================
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KnapsackSolver
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====================================
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Problem
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-------
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Subset sum problem
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Instance
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--------
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Number of items: 1000
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Capacity: 250000
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Algorithm
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---------
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Dynamic programming - Bellman - word RAM - recursive scheme
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Parameters
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----------
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Time limit: inf
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Messages
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Verbosity level: 1
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Standard output: 1
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File path:
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# streams: 0
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Logger
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Has logger: 0
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Standard error: 0
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File path:
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Time (s) Sol. Value Bound Gap Gap (%) Comment
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-------- ---- ----- ----- --- ------- -------
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0.000 1 0 250000 250000 100.00
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0.033 1 250000 250000 0 0.00 algorithm end (solution)
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Final statistics
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----------------
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Value: 250000
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Has solution: 1
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Bound: 250000
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Absolute optimality gap: 0
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Relative optimality gap (%): 0
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Time (s): 0.0330949
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Solution
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--------
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Number of items: 484 / 1000 (48.4%)
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Weight: 250000 / 250000 (100%)
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Feasible: 1
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```
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Run tests:
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```
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export KNAPSACK_DATA=$(pwd)/data/knapsack

‎extern/CMakeLists.txt‎

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# Fetch googletest.
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if(KNAPSACKSOLVER_BUILD_TEST)
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FetchContent_Declare(
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googletest
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URL https://github.com/google/googletest/archive/03597a01ee50ed33e9dfd640b249b4be3799d395.zip)
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# For Windows: Prevent overriding the parent project's compiler/linker settings
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set(gtest_force_shared_crt ON CACHE BOOL "" FORCE)
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set(INSTALL_GTEST OFF)
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FetchContent_MakeAvailable(googletest)
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FetchContent_Declare(
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googletest
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URL https://github.com/google/googletest/archive/03597a01ee50ed33e9dfd640b249b4be3799d395.zip)
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# For Windows: Prevent overriding the parent project's compiler/linker settings
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set(gtest_force_shared_crt ON CACHE BOOL "" FORCE)
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set(INSTALL_GTEST OFF)
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FetchContent_MakeAvailable(googletest)
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endif()
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# Fetch fontanf/optimizationtools.

include/knapsacksolver/knapsack/algorithm_formatter.hpp renamed to include/knapsacksolver/algorithm_formatter.hpp

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#pragma once
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#include "knapsacksolver/knapsack/solution.hpp"
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#include "knapsacksolver/solution.hpp"
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namespace knapsacksolver
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{
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namespace knapsack
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{
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class AlgorithmFormatter
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{
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};
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}
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}

include/knapsacksolver/knapsack/algorithms/dynamic_programming_bellman.hpp renamed to include/knapsacksolver/algorithms/dynamic_programming_bellman.hpp

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#pragma once
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#include "knapsacksolver/knapsack/solution.hpp"
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#include "knapsacksolver/solution.hpp"
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namespace knapsacksolver
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{
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namespace knapsack
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{
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Output dynamic_programming_bellman_rec(
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const Instance& instance,
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const DynamicProgrammingBellmanListParameters& parameters = {});
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}
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}

include/knapsacksolver/knapsack/algorithms/dynamic_programming_primal_dual.hpp renamed to include/knapsacksolver/algorithms/dynamic_programming_primal_dual.hpp

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#pragma once
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#include "knapsacksolver/knapsack/solution.hpp"
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#include "knapsacksolver/solution.hpp"
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namespace knapsacksolver
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{
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namespace knapsack
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{
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struct DynamicProgrammingPrimalDualParameters: Parameters
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{
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const DynamicProgrammingPrimalDualParameters& parameters = {});
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}
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}

include/knapsacksolver/knapsack/algorithms/greedy.hpp renamed to include/knapsacksolver/algorithms/greedy.hpp

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#pragma once
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#include "knapsacksolver/knapsack/solution.hpp"
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#include "knapsacksolver/knapsack/sort.hpp"
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#include "knapsacksolver/solution.hpp"
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#include "knapsacksolver/sort.hpp"
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namespace knapsacksolver
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{
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namespace knapsack
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{
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Output trivial(
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const Instance& instance,
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const GreedyParameters& parameters = {});
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}
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}

include/knapsacksolver/knapsack/algorithms/surrogate_relaxation.hpp renamed to include/knapsacksolver/algorithms/surrogate_relaxation.hpp

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#pragma once
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#include "knapsacksolver/knapsack/solution.hpp"
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#include "knapsacksolver/solution.hpp"
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namespace knapsacksolver
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{
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namespace knapsack
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{
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using SolveCallback = std::function<Output(const Instance&)>;
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const SurrogateRelaxationParameters& parameters = {});
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}
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}

include/knapsacksolver/knapsack/algorithms/upper_bound_dantzig.hpp renamed to include/knapsacksolver/algorithms/upper_bound_dantzig.hpp

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#pragma once
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#include "knapsacksolver/knapsack/solution.hpp"
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#include "knapsacksolver/knapsack/sort.hpp"
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#include "knapsacksolver/solution.hpp"
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#include "knapsacksolver/sort.hpp"
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namespace knapsacksolver
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{
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namespace knapsack
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{
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struct UpperBoundDantzigParameters: Parameters
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{
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const UpperBoundDantzigParameters& parameters = {});
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}
47-
}

include/knapsacksolver/knapsack/generator.hpp renamed to include/knapsacksolver/generator.hpp

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#pragma once
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#include "knapsacksolver/knapsack/instance.hpp"
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#include "knapsacksolver/instance.hpp"
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#include <random>
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namespace knapsacksolver
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{
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namespace knapsack
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{
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Instance generate_u(
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ItemPos number_of_items,
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std::mt19937_64& generator);
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}
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}

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