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If the only benefit were saving money and time in vacation planning, the difficulty of finding a minimum-cost Hamiltonian circuit in a complete graph with n vertices for large values of n would not be of great concern. However, the problem we are discussing is one of the most common in operations research, the branch of mathematics concerned with getting governments and businesses to operate more efficiently. This problem is usually called the traveling salesman problem (TSP) because of its early formulation.
Traveling Salesman Problem (TSP) DEFINITION
The traveling salesman problem (TSP) involves finding the trip of minimum cost that a salesman can make to visit the cities in a sales territory once and only once (represented by a complete graph with weights on the edges), starting and ending the trip in the same city.
Many situations require in essence solving a TSP:
Perhaps surprisingly, TSPs are also solved regularly in the design of computer chips. The components must be located so that the machines involved in the assembly can insert them on the chips as efficiently as possible. Because many chips are manufactured, even a small improvement in the time needed to make a chip can save a lot of money.
The meaning of cost can vary from one formulation of a TSP to another. We can measure cost as distance, airplane ticket prices, time, or any other factor that is to be optimized. In many situations, the TSP arises as a subproblem of a more complicated problem. For example, a supermarket chain may have a very large number of stores to be served from a single large warehouse. If there are fewer trucks than stores, the stores must be grouped into clusters so that one truck can serve each cluster. If we then solve the TSP for every truck, we can minimize total costs for the supermarket chain. Similar vehicle-routing problems—for dial-a-ride services that transport senior citizens to activity centers, for example, or that deliver children to their schools or camps—often involve solving the TSP as a subproblem.