Exact Methods for Solving Traveling Salesman Problems with Pickup and Delivery in Real Time

The Traveling Salesman Problem with Pickup and Delivery (TSPPD) describes the problem of finding a minimum cost path in which pickups precede their associated deliveries. The TSPPD is particularly important in the growing field of Dynamic Pickup and Delivery Problems (DPDP). These include the many-to-many Dial-A-Ride Problems (DARP) of companies such as Uber and Lyft, … Read more

The Traveling Salesperson Problem with Forbidden Neighborhoods on Regular 3D Grids

We study the traveling salesperson problem with forbidden neighborhoods (TSPFN) on regular three-dimensional grids. The TSPFN asks for a shortest tour over all grid points such that successive points along a tour have at least some given distance. We present optimal solutions and explicit construction schemes for the Euclidean TSP and the TSPFN where edges … Read more

Closed Almost Knight’s Tours on 2D and 3D Chessboards

Let a (generalized) chessboard in two or three dimensions be given. A closed knight’s tour is defined as a Hamiltonian cycle over all cells of the chessboard where all moves are knight’s moves, i.,e. have length 5^0.5. It is well-characterized for which chessboard sizes it is not possible to construct a closed knight’s tour. On … Read more

The Traveling Salesman Problem on Grids with Forbidden Neighborhoods

We introduce the Traveling Salesman Problem with forbidden neighborhoods (TSPFN). This is an extension of the Euclidean TSP in the plane where direct connections between points that are too close are forbidden. The TSPFN is motivated by an application in laser beam melting. In the production of a workpiece in several layers using this method … Read more

Minimization and Maximization Versions of the Quadratic Traveling Salesman Problem

The traveling salesman problem (TSP) asks for a shortest tour through all vertices of a graph with respect to the weights of the edges. The symmetric quadratic traveling salesman problem (SQTSP) associates a weight with every three vertices traversed in succession. If these weights correspond to the turning angles of the tour, we speak of … Read more

Constructing a Small Compact Binary Model for the Travelling Salesman Problem

A variety of formulations for the Travelling Salesman Problem as Mixed Integer Program have been proposed. They contain either non-binary variables or the number of constraints and variables is large. We want to give a new formulation that consists solely of binary variables; the number of variables and the number of constraints are of order … Read more

The Time Dependent Traveling Salesman Planning Problem in Controlled Airspace

The integration of Unmanned Aircraft Systems (UAS) into civil airspace is one of the most challenging problems for the automation of the Controlled Airspace, and the optimization of the UAS route is a key step for this process. In this paper, we optimize the planning phase of a UAS mission that consists of departing from … Read more

Generating subtour constraints for the TSP from pure integer solutions

The traveling salesman problem (TSP) is one of the most prominent combinatorial optimization problems. Given a complete graph G = (V, E) and nonnegative real edge distances d, the TSP asks for a shortest tour through all vertices with respect to the distances d. The method of choice for solving the TSP to optimality is … Read more

Equivalence of an Approximate Linear Programming Bound with the Held-Karp Bound for the Traveling Salesman Problem

We consider two linear relaxations of the asymmetric traveling salesman problem (TSP), the Held-Karp relaxation of the TSP’s arc-based formulation, and a particular approximate linear programming (ALP) relaxation obtained by restricting the dual of the TSP’s shortest path formulation. We show that the two formulations produce equal lower bounds for the TSP’s optimal cost regardless … Read more

Multidirectional Physarum Solver: an Innovative Bio-inspired Algorithm for Optimal Discrete Decision Making

This paper introduces a new bio-inspired algorithm for optimal discrete decision making, able to incrementally grow and explore decision graphs in multiple directions. The heuristic draws inspiration from the idea that building decision sequences from multiple directions and then combining the sequences is an optimal choice if compared with a unidirectional approach. The behaviour of … Read more