Dynamic Traveling Salesman Problem Jan Fbry University of
Dynamic Traveling Salesman Problem Jan Fábry University of Economics Prague ___________________________________________ MME 2006, Pilsen 1
Standard TSP (Static) All customers are known before start of travel Dynamic TSP Some requirements arrive after start of travel ___________________________________________ MME 2006, Pilsen 2
Static TSP (Miler-Tucker-Zemlin) minimize subject to ___________________________________________ MME 2006, Pilsen 3
Static TSP Example 2 4 Optimal Route 5 1 Depot 6 3 ___________________________________________ MME 2006, Pilsen 4
Dynamic TSP Example 2 4 7 Depot 1 New customer 5 6 3 ___________________________________________ MME 2006, Pilsen 5
Dynamic TSP A new customer Re-optimization of the route Insertion algorithm ___________________________________________ MME 2006, Pilsen 6
Dynamic TSP Re-optimization of the route minimize subject to Set of locations to be visited ___________________________________________ MME 2006, Pilsen 7
Dynamic TSP Example 2 7 New customer 4 5 Depot 1 6 3 ___________________________________________ MME 2006, Pilsen 8
Dynamic TSP Insertion algorithm Sequence of locations to be visited r ik ik+1 ___________________________________________ MME 2006, Pilsen 9
TSP with Time Windows minimize subject to ___________________________________________ MME 2006, Pilsen 10
TSP with Time Windows Waiting times included Change of the model: minimize ___________________________________________ MME 2006, Pilsen 11
Dynamic TSP with Time Windows A new customer Re-optimization of the route Insertion algorithm ___________________________________________ MME 2006, Pilsen 12
Dynamic TSP with Time Windows Re-optimization of the route minimize subject to (to be continued…) ___________________________________________ MME 2006, Pilsen 13
Dynamic TSP with Time Windows Re-optimization of the route ___________________________________________ MME 2006, Pilsen 14
Dynamic TSP with Time Windows Insertion algorithm Sequence of customers to be visited ___________________________________________ MME 2006, Pilsen 15
Dynamic TSP with Time Windows Insertion algorithm ___________________________________________ MME 2006, Pilsen 16
TSP with Time Windows „Hard“ windows „Soft“ windows Penalties minimize ___________________________________________ MME 2006, Pilsen 17
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