Publication | Open Access
AN ALGORITHM FOR SINGLE CONSTRAINT MAXIMUM COLLECTION PROBLEM
75
Citations
8
References
1988
Year
Mathematical ProgrammingEngineeringNetwork AnalysisComputational ComplexityAssignment ProblemOperations ResearchConstraint ProgrammingVehicle RoutingConstraint SolvingTraveling Salesman ProblemLogisticsSystems EngineeringDiscrete MathematicsCombinatorial OptimizationTransportation EngineeringComputer ScienceInteger ProgrammingRoute ChoiceNetwork Routing AlgorithmNetwork ScienceGraph TheoryConstraint SatisfactionRoute PlanningOptimal TourBusinessVehicle Routing ProblemHeuristic Search
There are many studies which consider an optimal tour on a given graph including the well-known Traveling Salesman Problem (TSP) and Vehicle Routing Problem (VRP). Most of these studies, however, assume that "all" nodes on a given graph should be visited exactly once or at least once. In this paper, we relax this assumption and consider the following problem: "Given items with known values located at nodes of network, one wants to collect items so that their total value is maximized, under the assumption that a tour starting from the "center" node and returning to the center node is completed within a predetermined time limit." Because of the added (time) constraint, one may not visit all nodes. The addition of this simple-looking constraint makes the problem difficult as it introduces an added dimention of selecting nodes to visit. After a brief introduction, Section 2 presents two formulations of the problem, a native formulation and an improved one based on the introduction of self-loops to the graph corresponding to the problem. The latter formulation allows us to utilize solution strategies developed for the standard TSP. A branch and bound solution strategies together with a solution method of a relaxation problem is described in Section 3. A relaxation problem is generally an assignment problem with an added constraint for which an efficient branch and bound procedure is proposed. In particular, a recommended strategy for the selection of the branching variable is identified, and also an efficient procedure to transmit information from a branching problem to its sub-problems is proposed. Section 4 presents results of computational time requirements and basic characteristics of the proposed algorithm are clarified.
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