We consider the one-to-one Pickup and Delivery Problem (PDP) in Euclidean Space with arbitrary dimension @math where @math transportation requests are picked i.i.d. with a separate origin-destination pair for each object to be moved. First, we consider the problem from the customer perspective where the objective is to compute a plan for transporting the objects such that the Euclidean distance traveled by the vehicles when carrying objects is minimized. We develop a polynomial time asymptotically optimal algorithm for vehicles with capacity @math for this case. This result also holds imposing LIFO constraints for loading and unloading objects. Secondly, we extend our algorithm to the classical single-vehicle PDP where the objective is to minimize the total distance traveled by the vehicle and present results indicating that the extended algorithm is asymptotically optimal for a fixed vehicle capacity if the origins and destinations are picked i.i.d. using the same distribution.
As noted by many authors, the PDP problem generalizes the classical TSP problem and is thus NP complete for @math . Guan @cite_4 has shown that the PDP problem is NP complete for @math and @math and Guan also shows how to solve this version in linear time if we allow temporarily dropping objects. @cite_0 present asymptotically optimal algorithms for @math (SCP) and @math where the origins are picked i.i.d. and the destinations are picked i.i.d. from separate distributions.
@cite_0 @cite_4
2241606427 2000628435
Consider the problem of transporting a set of objects between the vertices of a path by a vehicle which has limited capacity. The problem of finding a shortest tour for the vehicle to transport all objects from their initial vertices to their destination vertices is a fundamental problem in motion planning. It is shown that the problem is NP-complete if every object must be transported directly from its initial vertex to its destination. However, if objects can be dropped at intermediate vertices along its tour and picked up later then the problem can be solved in linear time. It is also shown that if the underlying graph is a tree, instead of a path, then the problem is NP-complete even if objects can be dropped at intermediate vertices. In this paper we study noisy sorting without re-sampling. In this problem there is an unknown order @math for all pairs @math , where @math is a constant and @math for all @math and @math . It is assumed that the errors are independent. Given the status of the queries the goal is to find the maximum likelihood order. In other words, the goal is find a permutation @math that minimizes the number of pairs @math where @math . The problem so defined is the feedback arc set problem on distributions of inputs, each of which is a tournament obtained as a noisy perturbations of a linear order. Note that when @math and @math is large, it is impossible to recover the original order @math . It is known that the weighted feedback are set problem on tournaments is NP-hard in general. Here we present an algorithm of running time @math and sampling complexity @math that with high probability solves the noisy sorting without re-sampling problem. We also show that if @math is an optimal solution of the problem then it is close'' to the original order. More formally, with high probability it holds that @math and @math . Our results are of interest in applications to ranking, such as ranking in sports, or ranking of search items based on comparisons by experts. We consider the following variants of the bandwidth minimization problem: (1) the cycle-bandwidth problem which for a given graph G and positive integer k, asks if there is a circular layout such that every pair of adjacent vertexes have a distance at most k, (2) the separation problem which asks if there is a linear layout such that every pair of adjacent vertexes have a distance greater than k, and (3) the cycle-separation problem which asks if there is a circular layout such that every pair of adjacent vertexes have a distance greater than k.We show that the cycle-bandwidth problem is NP-complete for each fixed @math the separation and cycle-separation problems are both NP-complete for each fixed @math , and the directed separation problem is NP-complete for arbitrary k. We give polynomial time algorithms for several special cases of the directed separation problem. Finally, we show the relationships of the directed separation problem with several scheduling problems by giving reduct... The Near-Bipartiteness problem is that of deciding whether or not the vertices of a graph can be partitioned into sets @math and @math , where @math is an independent set and @math induces a forest. The set @math in such a partition is said to be an independent feedback vertex set. Yang and Yuan proved that Near-Bipartiteness is polynomial-time solvable for graphs of diameter 2 and NP-complete for graphs of diameter 4. We show that Near-Bipartiteness is NP-complete for graphs of diameter 3, resolving their open problem. We also generalise their result for diameter 2 by proving that even the problem of computing a minimum independent feedback vertex is polynomial-time solvable for graphs of diameter 2.