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< h1 > or-tools/examples/cpp/< / h1 >
< p >
This is the main page of the auto-generated documentation for directory < code > or-tools/examples/cpp/< / code > . < br >
Please use the tabs just above the title to navigate documentation in this directory.< h2 > < a class = "anchor" name = "Readme" >
Readme< / a > < / h2 >
< em > From < code > or-tools/examples/cpp/README< / code > :< / em > < br >
C++ examples to demonstrate usage of the different< br >
Operations Research libraries.< br >
< br >
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< ul >
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< li > Constraint Solver examples:< br >
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< ul >
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< li > < a class = "el" href = "cryptarithm_8cc.html" > cryptarithm.cc< / a > Demonstrates the use of basic modeling objects< br >
(integer variables, arithmetic constraints and expressions,< br >
simple search).< br >
< / li > < li > < a class = "el" href = "golomb_8cc.html" > golomb.cc< / a > Demonstrates how to handle objective functions and collect< br >
solutions found during the search.< br >
< / li > < li > < a class = "el" href = "magic__square_8cc.html" > magic_square.cc< / a > Shows how to use the automatic search to solve your< br >
problem.< br >
< / li > < li > < a class = "el" href = "costas__array_8cc.html" > costas_array.cc< / a > Solves the problem of Costas Array (a constrained< br >
assignment problem used for radars) with two version. On version is< br >
a feasibility version with hard constraints, the other version is< br >
an optimization version with soft constraints and violation costs.< br >
< / li > < li > < a class = "el" href = "jobshop_8cc.html" > jobshop.cc< / a > Demonstrates scheduling of jobs on different machines.< br >
< / li > < li > < a class = "el" href = "jobshop__ls_8cc.html" > jobshop_ls.cc< / a > Demonstrates scheduling of jobs on different machines with< br >
a search using Local Search and Large Neighorhood Search.< br >
< / li > < li > < a class = "el" href = "nqueens_8cc.html" > nqueens.cc< / a > Solves the n-queen problem. It also demonstrates how to break< br >
symmetries during search.< br >
< / li > < li > < a class = "el" href = "network__routing_8cc.html" > network_routing.cc< / a > Solves a multicommodity mono-routing< br >
problem with capacity constraints and a max usage cost structure.< br >
< / li > < li > < a class = "el" href = "sports__scheduling_8cc.html" > sports_scheduling.cc< / a > Finds a soccer championship schedule. Its uses an< br >
original approach where all constraints attached to either one team,< br >
or one week are regrouped into one global 'AllowedAssignment' constraints.< br >
< / li > < li > < a class = "el" href = "dobble__ls_8cc.html" > dobble_ls.cc< / a > Shows how to write Local Search operators and Local Search< br >
filters in a context of an assignment/partitioning problem. It also< br >
shows how to write a simple constraint.< br >
< br >
< / li > < / ul >
< / li > < li > Routing examples:< br >
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< ul >
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< li > < a class = "el" href = "tsp_8cc.html" > tsp.cc< / a > Travelling Salesman Problem.< br >
< / li > < li > < a class = "el" href = "cvrptw_8cc.html" > cvrptw.cc< / a > Capacitated Vehicle Routing Problem with Time Windows.< br >
< / li > < li > carptw.cc Capacitated Vehicle Arc-Routing Problem with Time Windows.< br >
< / li > < li > < a class = "el" href = "pdptw_8cc.html" > pdptw.cc< / a > Pickup and Delivery Problem with Time Windows.< br >
< br >
< / li > < / ul >
< / li > < li > Graph examples:< br >
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< ul >
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< li > < a class = "el" href = "flow__api_8cc.html" > flow_api.cc< / a > Demonstrates how to use Min-Cost Flow and Max-Flow api.< br >
< / li > < li > < a class = "el" href = "linear__assignment__api_8cc.html" > linear_assignment_api.cc< / a > Demonstrates how to use the Linear Sum< br >
Assignment solver.< br >
< / li > < li > < a class = "el" href = "dimacs__assignment_8cc.html" > dimacs_assignment.cc< / a > Solves DIMACS challenge on assignment< br >
problems.< br >
< br >
< / li > < / ul >
< / li > < li > Linear and integer programming examples:< br >
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< ul >
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< li > < a class = "el" href = "linear__programming_8cc.html" > linear_programming.cc< / a > Demonstrates how to use the linear solver< br >
wrapper API to solve Linear Programming problems.< br >
< / li > < li > < a class = "el" href = "integer__programming_8cc.html" > integer_programming.cc< / a > Demonstrates how to use the linear solver< br >
wrapper API to solve Integer Programming problems.< br >
< / li > < li > < a class = "el" href = "linear__solver__protocol__buffers_8cc.html" > linear_solver_protocol_buffers.cc< / a > Demonstrates how protocol< br >
buffers can be used as input and output to the linear solver wrapper.< br >
< / li > < li > < a class = "el" href = "strawberry__fields__with__column__generation_8cc.html" > strawberry_fields_with_column_generation.cc< / a > Complex example that< br >
demonstrates how to use dynamic column generation to solve a 2D< br >
covering problem.< br >
< br >
< / li > < / ul >
< / li > < li > Examples using multiple technologies:< br >
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< ul >
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< li > warehouse_run.cc Solve a capacitated warehouse location problem with< br >
different techniques.< br >
< br >
< / li > < / ul >
< / li > < li > Utilities< br >
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< ul >
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< li > < a class = "el" href = "model__util_8cc.html" > model_util.cc< / a > A utility to manipulate model files (.cp) dumped by the< br >
solver.< br >
< / li > < / ul >
< / li > < / ul >
< h2 > < a class = "anchor" name = "Owners" >
Owners< / a > < / h2 >
< em > There is no < code > OWNERS< / code > in this directory.< / em > < / div >
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