We present a natural fitness function f for the multiobjective shortest path problem, which is a fundamental multiobjective combinatorial optimization problem known to be NP-hard. Thereafter, we conduct a rigorous runtime analysis of a simple evolutionary algorithm (EA) optimizing f . Interestingly, this simple general algorithm is a fully polynomial-time randomized approximation scheme (FPRAS)...

We study the minimum spanning tree problem, the maximum matching problem and the shortest path problem subject to binary disjunctive constraints: A negative disjunctive constraint states that a certain pair of edges cannot be contained simultaneously in a feasible solution. It is convenient to represent these negative disjunctive constraints in terms of a so-called conflict graph whose vertices...

Recoverable robustness is a concept to avoid over-conservatism in robust optimization by allowing a limited recovery after the full data is revealed. We investigate two settings of recoverable robust shortest path problems. In both settings the costs of the arcs are subject to uncertainty. For the first setting, at most k arcs of the chosen path can be altered in the recovery. In the second set...

Shortest path computation is a classical combinatorial optimization problem. Neural networks, as a class of effective optimization approaches, have been used for processing path optimization problems for a long time. Pulse Coupled Neural Network (PCNN) is a very different neural network, which has also been proposed to compute shortest paths in recent years. In some existing PCNN models, the co...

Long distance truck drivers in Sub-Saharan Africa are extremely vulnerable to HIV and other infectious diseases. The NGO North Star Alliance aims to alleviate this situation by placing so-called Roadside Wellness Centers (RWCs) at busy truck stops along major truck routes. Currently, locations for new RWCs are chosen so as to maximize the expected patient volume and to ensure continuity of acce...