We consider a multiple-vehicle routing problem with split pick-ups (mVRPSP). This problem involves multiple suppliers, a single depot, and a fleet of identical capacity trucks responsible for delivering supplies from ...
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We consider a multiple-vehicle routing problem with split pick-ups (mVRPSP). This problem involves multiple suppliers, a single depot, and a fleet of identical capacity trucks responsible for delivering supplies from the suppliers to the depot. Any supplier may be visited by more than one truck, thus allowing split pick-ups. The problem is to determine, for each truck, which suppliers to visit and the size of loads to pick up so as to minimize the total transportation cost for the fleet, which depends on the number of trucks used and their routes. We develop a fundamentally new model for the mVRPSP, a deterministic dynamic program (DP). Although the most natural DP formulation results in a DP with uncountably-infinite state and action spaces, an optimality-invariance condition we establish leads to an equivalent DP with finite state and action spaces. This DP formulation leads to a new exact algorithm for solving the mVRPSP, based on a shortestpath search algorithm, which is conceptually simple and easy to implement. Crown Copyright (c) 2005 Published by Elsevier Ltd. All rights reserved.
It is the truth that spending life on the road is not fun. Therefore, every driver is searching for the "shortestpath" for their traveling. Since the real objective is the smallest time frame that the drive...
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ISBN:
(纸本)9781424400997
It is the truth that spending life on the road is not fun. Therefore, every driver is searching for the "shortestpath" for their traveling. Since the real objective is the smallest time frame that the driver spends on the road before arriving at the required destination. Various methods have been proposed to solve the problem of this shortestpath under the hierarchical index road network. Unfortunately that none of them has considered the situation of traveling in the congestion traffic mode. This paper presents a solution, called an adaptive travel-time path selection algorithm, to obtain the shortestpath where the shortest travel-time has been achieved. The experiment had shown that the selected path obtaining from the proposed algorithm has less time complexity than the previous existing methods.
This paper presents new algorithms for computing shortestpaths in a nearly acyclic directed graph G = (V, E). The new algorithms improve on the worst-case running time of previous algorithms. Such algorithms use the ...
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ISBN:
(纸本)1920682236
This paper presents new algorithms for computing shortestpaths in a nearly acyclic directed graph G = (V, E). The new algorithms improve on the worst-case running time of previous algorithms. Such algorithms use the concept of a 1-dominator set. A 1-dominator set divides the graph into a unique collection of acyclic subgraphs, where each acyclic subgraph is dominated by a single associated trigger vertex. The previous time for computing a 1-dominator set is improved from O(mn) to O(m), where m = |E| and n = |V|. Efficient shortest path algorithms only spend delete-min operations on trigger vertices, thereby making the computation of shortestpaths through non-trigger vertices easier. Under this framework, the time complexity for the all-pairs shortestpath (APSP) problem is improved from O(mn + nr log r) to O(mn + r2 log r), where r is the number of triggers. Here the second term in the complexity results from delete-min operations in a heap of size r. The time complexity of the APSP problem on the broader class of nearly acyclic graphs, where trigger vertices correspond to any precomputed feedback vertex set, is similarly improved from O(mn + nr2) to O(mn + r3). This paper also mentions that the 1-dominator set concept can be generalised to define a bidirectional 1-dominator set and k-dominator sets.
The design of complex systems can involve the selection of several subsystem designs. We investigate the problem of selecting discrete concepts from multiple, coupled subsystems. This problem is one where measures of ...
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The design of complex systems can involve the selection of several subsystem designs. We investigate the problem of selecting discrete concepts from multiple, coupled subsystems. This problem is one where measures of merit for both subsystem (local) and system (global) levels are present. An approach is developed to obtain the sets of preferred subsystem design concepts. Graph theory is used to represent the coupled selection problem where the nodes of the graph are the subsystem design choices and the arcs connecting the nodes indicate the relationships between the subsystems. Optimization techniques from graph theory and physical programming are combined to form an approach to model and solve this problem. This approach can be used to identify a given number of successful, or feasible, subsystem combinations that represent design alternatives. Once the promising subsystem designs are obtained at the conceptual design stage, focus can be restricted to these chosen design alternatives for further testing and refinement at a later embodiment design stage. Although the examples presented in this paper involve conceptual design, the presented approach can be used with any coupled discrete selection problem.
shortest path algorithms are required by several transportation applications;furthermore, the shortestpath computation in these applications can account for a large percentage of the total execution time. Since these...
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shortest path algorithms are required by several transportation applications;furthermore, the shortestpath computation in these applications can account for a large percentage of the total execution time. Since these algorithms are very computationally intense, parallel processing can provide the compute power and memory required to solve large problems quickly. Therefore, good parallel shortestalgorithms are critical for efficient parallel implementations of transportation applications. The experimental work related to parallel shortest path algorithms has focused on the development of parallel algorithms;however, very little work has been done with analyzing and understanding the performance impact of various implementation issues. In this paper, we conduct a thorough experimental analysis of parallel shortest path algorithms for sparse networks, concentrating on three implementation issues: (1) choice of shortestpath algorithm, (2) termination detection and (3) network decomposition. The paper focuses on the choice of shortestpath algorithm and network decomposition since the work on termination detection was published previously. We determine that all three issues affect the communication and convergence of the shortestpath algorithm. Furthermore, we find that communicating the most information at a time results in the best convergence;this is contrary to most scientific applications where it is optimal to minimize communication. (C) 2001 Published by Elsevier Science B.V.
We consider bipartite matching algorithms for computing permutations of a sparse matrix so that the diagonal of the permuted matrix has entries of large absolute value. We discuss various strategies for this and consi...
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We consider bipartite matching algorithms for computing permutations of a sparse matrix so that the diagonal of the permuted matrix has entries of large absolute value. We discuss various strategies for this and consider their implementation as computer codes. We also consider scaling techniques to further increase the relative values of the diagonal entries. Numerical experiments show the effect of the reorderings and the scaling on the solution of sparse equations by a direct method and by preconditioned iterative techniques.
In this paper, we present a time-dependent intermodal optimum path algorithm for multimodal transportation networks that accounts for delays at mode and are switching points, The correctness and computational complexi...
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In this paper, we present a time-dependent intermodal optimum path algorithm for multimodal transportation networks that accounts for delays at mode and are switching points, The correctness and computational complexity of the algorithm are proved. A simple representation of the mode-to-mode switching options is introduced that results in a substantially improved design, with computational complexity independent of the number of modes and fixed schedule lines for typical transit and freight networks. The algorithm is implemented, coded, and computationally tested on realistic size networks with promising results. (C) 2000 Elsevier Science B.V. All rights reserved.
The watershed line is the basic tool for segmenting images in mathematical morphology. A rigorous definition is given in terms of a distance function called topographic distance. If the topographical function is itsel...
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The watershed line is the basic tool for segmenting images in mathematical morphology. A rigorous definition is given in terms of a distance function called topographic distance. If the topographical function is itself a distance function, then the topographical distance becomes identical with the geodesic distance function and the watershed becomes identical with the skeleton by zone of influence. The classical shortestpaths algorithms of the graph theory are then revisited in order to derive new watershed algorithms, which are either new or more easy to implement in hardware.
A new distributed algorithm is presented that can be used to solve the single-destination shortestpath (SDSP) problem or the all-pairs shortestpath (APSP) problem for a class of clustered data networks. The network ...
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A new distributed algorithm is presented that can be used to solve the single-destination shortestpath (SDSP) problem or the all-pairs shortestpath (APSP) problem for a class of clustered data networks. The network graph is assumed to be characterized with a balanced hierarchically clustered (BHC) topology. The BHC topology is introduced in this paper and is shown to be a realistic characterization for a large class of interconnected data networks. For certain types of BHC topologies, the SDSP problem can be solved with computation and communication time complexities of O(log n), assuming one processor is available at each of the n number of nodes. Assuming p processors are available at each node, computation and communication time complexities of O((n/p)log n) and O(n log n) are achievable, respectively, for solving the APSP problem. It is also shown that the algorithm converges in an asynchronous environment. Therefore, some of the difficulties associated with synchronizing the order of events can be avoided in the actual implementation of the proposed algorithm.
The Thresh X2 algorithm has been shown to dominate other shortest path algorithms over a wide variety of conditions. When used on random networks which have exponentially or normally distributed edge weights the perfo...
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The Thresh X2 algorithm has been shown to dominate other shortest path algorithms over a wide variety of conditions. When used on random networks which have exponentially or normally distributed edge weights the performance of X2 degrades. We develop techniques which improve X2's performance up to 33% in these cases.
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