scholarly journals Optimizing the Paths of Trains Formed at the Loading Area in a Multi-loop Rail Network

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 844
Author(s):  
Xingkui Li ◽  
Boliang Lin ◽  
Yinan Zhao
Keyword(s):  
Genetic Algorithm ◽  
Branch And Bound ◽  
Large Scale ◽  
Path Selection ◽  
Branch And Bound Algorithm ◽  
Computational Experiments ◽  
Commercial Software ◽  
Rail Network ◽  
Selection For

Each loop in a multi-loop rail network consists of two segments, both of which have roughly the same conditions and mileage and are approximately symmetrical. This paper is devoted to optimizing the paths of trains formed at the loading area in a multi-loop rail network. To attain this goal, three different situations are analyzed, and two models are proposed for networks with adequate and inadequate capabilities. Computational experiments are also carried out using the commercial software Lingo, with the branch and bound algorithm. The results show that the models can achieve the same solution with different solution times. To solve the problem of path selection for large-scale train flows, a genetic algorithm is also designed and proves to perform well in a set of computational experiments.

Optimal Phasor Measurement Unit Placement for Numerical Observability Using A Two-Phase Branch-and-Bound Algorithm

2018 ◽  
Vol 19 (3) ◽  
Author(s):  
Nikolaos P. Theodorakatos
Keyword(s):  
Branch And Bound ◽  
Large Scale ◽  
Global Solutions ◽  
Efficient Solutions ◽  
Point Of View ◽  
Branch And Bound Algorithm ◽  
Mixed Integer ◽  
Measurement Unit ◽  
Two Phase ◽  
Phasor Measurement

Abstract Given an undirected graph representing the network, the optimization problem of finding the minimum number of phasor measurement units to place on the edges such that the graph is fully observed, is studied. The proposal addresses the issue of the optimization using a two-phase branch-and-bound algorithm based on combining both Depth-First Search and Breadth-First Search algorithms to attempt to find guaranteed global solutions for OPP. The problem in question is stated, outlining the underlying mathematical model in use formulated in terms of (pure) mixed-integer-linear-programming (MILP) and the branch-and-bound algorithm adopted to obtain efficient solutions in practice. A topology based on transformations considering pre-existing conventional and zero injection measurements in a power network is implemented. The (zero-one) (MILP) model is applied to IEEE systems. The numerical results indicate that the branch-and-bound ensures solution points at the optimal objective function value from a global-optimization point of view. The synchronized and conventional measurements are included in a (DC) linearized State Estimator (SE). The topological observability analysis is verified numerically based on observability criteria for achieving solvability of state estimation. Large-scale systems is also analyzed to exhibit the applicability of the proposed algorithm to practical power system cases.

scholarly journals A BRANCH AND BOUND ALGORITHM FOR WORKFLOW SCHEDULING

2018 ◽  
Vol 56 (2) ◽  
pp. 246
Author(s):  
Phan Thanh Toan ◽  
Nguyen The Loc
Keyword(s):  
Branch And Bound ◽  
Large Scale ◽  
Resource Constraints ◽  
Data Transfer ◽  
Scheduling Algorithm ◽  
Large Data ◽  
Scientific Workflow ◽  
Branch And Bound Algorithm ◽  
Workflow Scheduling ◽  
Tools And Techniques

Nowadays, people are connected to the Internet and use different Cloud solutions to store, process and deliver data. The Cloud consists of a collection of virtual servers that promise to provision on-demand computational and storage resources when needed. Workflow data is becoming an ubiquitous term in both science and technology and there is a strong need for new  tools and techniques to process and analyze large-scale complex datasets that are growing exponentially. scientific workflow is a sequence of connected tasks with large data transfer from parent task to children tasks. Workflow scheduling is the activity of assigning tasks to execution on servers and satisfying resource constraints and this is an NP-hard problem. In this paper, we propose a scheduling algorithm for workflow data that is derived from the Branch and Bound Algorithm.

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