We study the computational complexity of some special partial inverse combinatorial optimization problems where the goal is to change a parameter at minimum cost such that there exists an optimal solution for the underlying combinatorial optimization problem with respect to the modified parameter that does not contain a prespecified set of forbidden elements. We show that the partial inverse pr...

An stochastic version of the classical shortest path problem whereby for each node of a graph, a probability distribution over the set of successor nodes must be chosen so as to reach a certain destination node with minimum expected cost. In this paper, we propose a new algorithm based on Particle Swarm Optimization (PSO) for solving Stochastic Shortest Path Problem (SSPP). The comparison of ou...

In this paper we broadly generalize the assignment auction algorithm to solve linear minimum cost network flow problems. We introduce a generic algorithm, which contains as special cases a number of known algorithms, including the e-relaxation method, and the auction algorithm for assignment and for transportation problems. The generic algorithm can serve as a broadly useful framework for the d...

Path planning method for unmanned underwater vehicles (UUV) homing and docking in movement disorders environment is proposed in this paper. Firstly, cost function is proposed for path planning. Then, a novel particle swarm optimization (NPSO) is proposed and applied to find the waypoint with minimum value of cost function. Then, a strategy for UUV enters into the mother vessel with a fixed angl...

The Traveling Deliveryman Problem is a generalization of the Minimum Cost Hamiltonian Path Problem where the starting vertex of the path, i.e. a depot vertex, is fixed in advance and the cost associated with a Hamiltonian path equals the sum of the costs for the layers of paths (along the Hamiltonian path) going from the depot vertex to each of the remaining vertices. In this paper, we propose ...

in this paper the concept of the minimum universal cost flow (mucf) for an infeasible flow network is introduced. a new mathematical model in which the objective function includes the total costs of changing arc capacities and sending flow is built and analyzed. a polynomial time algorithm is presented to find the mucf.

In this paper the concept of the Minimum Universal Cost Flow (MUCF) for an infeasible flow network is introduced. A new mathematical model in which the objective function includes the total costs of changing arc capacities and sending flow is built and analyzed. A polynomial time algorithm is presented to find the MUCF.