scholarly journals Corrigendum to “Least Expected Time Paths in Stochastic Schedule-Based Transit Networks”

2018 ◽  
Vol 2018 ◽  
pp. 1-1
Author(s):  
Dang Khoa Vo ◽  
Tran Vu Pham ◽  
Nguyen Huynh Tuong ◽  
Van Hoai Tran
Keyword(s):  
Transit Networks ◽  
Expected Time ◽  
Stochastic Schedule

scholarly journals Least Expected Time Paths in Stochastic Schedule-Based Transit Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Dang Khoa Vo ◽  
Tran Vu Pham ◽  
Nguyen Huynh Tuong ◽  
Van Hoai Tran
Keyword(s):  
Arrival Times ◽  
Transit Network ◽  
Expected Time ◽  
City Bus ◽  
Time Operation ◽  
Real Time Operation ◽  
Total Travel Time ◽  
Dependent Model ◽  
Time Dependent Model ◽  
Stochastic Schedule

We consider the problem of determining a least expected time (LET) path that minimizes the number of transfers and the expected total travel time in a stochastic schedule-based transit network. A time-dependent model is proposed to represent the stochastic transit network where vehicle arrival times are fully stochastically correlated. An exact label-correcting algorithm is developed, based on a proposed dominance condition by which Bellman’s principle of optimality is valid. Experimental results, which are conducted on the Ho Chi Minh City bus network, show that the running time of the proposed algorithm is suitable for real-time operation, and the resulting LET paths are robust against uncertainty, such as unknown traffic scenarios.

Harry Beck's London Underground Map

Transfers ◽  
2014 ◽  
Vol 4 (2) ◽  
pp. 86-103 ◽  
Author(s):  
John D. Schwetman
Keyword(s):  
Urban Communities ◽  
Transit Networks ◽  
The World ◽  
London Underground ◽  
Societal Structure ◽  
The City

After Harry Beck designed his map of the London Underground, it became an icon of the city and a model for maps in other large transit networks around the world. The map allowed its readers to see themselves as components of the large, organized structure of the metropolis but also confronted them with the possibility of losing themselves to that structure. An analysis of the post-Beck subway map tradition shows it to be a battleground between the zeal for order and the latent chaos at the heart of the urban communities that the map represents and also situates this conflict in a larger context of the emergence of a global societal structure bound together by the control of capital and of the information that enables such control.

scholarly journals Asymptotic Expansions and Strategies in the Online Increasing Subsequence Problem

2021 ◽  
Vol 174 (1) ◽  
Author(s):  
Amirlan Seksenbayev
Keyword(s):  
Dynamic Programming ◽  
Asymptotic Expansions ◽  
Dual Problem ◽  
Infinite Length ◽  
Expected Time ◽  
Selection Strategies ◽  
Dynamic Programming Equation ◽  
Optimal Values ◽  
Design Selection ◽  
Selection Of

AbstractWe study two closely related problems in the online selection of increasing subsequence. In the first problem, introduced by Samuels and Steele (Ann. Probab. 9(6):937–947, 1981), the objective is to maximise the length of a subsequence selected by a nonanticipating strategy from a random sample of given size $n$ n . In the dual problem, recently studied by Arlotto et al. (Random Struct. Algorithms 49:235–252, 2016), the objective is to minimise the expected time needed to choose an increasing subsequence of given length $k$ k from a sequence of infinite length. Developing a method based on the monotonicity of the dynamic programming equation, we derive the two-term asymptotic expansions for the optimal values, with $O(1)$ O ( 1 ) remainder in the first problem and $O(k)$ O ( k ) in the second. Settling a conjecture in Arlotto et al. (Random Struct. Algorithms 52:41–53, 2018), we also design selection strategies to achieve optimality within these bounds, that are, in a sense, best possible.

A schedule-based timetable model for congested transit networks

2021 ◽  
Vol 124 ◽  
pp. 102925
Author(s):  
Jiemin Xie ◽  
Shuguang Zhan ◽  
S.C. Wong ◽  
S.M. Lo
Keyword(s):  
Transit Networks

scholarly journals The Rate of Compensatory Evolution

Genetics ◽  
1996 ◽  
Vol 144 (1) ◽  
pp. 419-426 ◽  
Author(s):  
Wolfgang Stephan
Keyword(s):  
Diffusion Theory ◽  
Secondary Structures ◽  
Compensatory Mutation ◽  
Weak Selection ◽  
Mutation Pressure ◽  
Theory Of Evolution ◽  
Compensatory Evolution ◽  
Expected Time ◽  
Individual Fitness ◽  
Shifting Balance

Abstract A two-locus model is presented to analyze the evolution of compensatory mutations occurring in stems of RNA secondary structures. Single mutations are assumed to be deleterious but harmless (neutral) in appropriate combinations. In proceeding under mutation pressure, natural selection and genetic drift from one fitness peak to another one, a population must therefore pass through a valley of intermediate deleterious states of individual fitness. The expected time for this transition is calculated using diffusion theory. The rate of compensatory evolution, kc, is then defined as the inverse of the expected transition time. When selection against deleterious single mutations is strong, kc, depends on the recombination fraction r between the two loci. Recombination generally reduces the rate of compensatory evolution because it breaks up favorable combinations of double mutants. For complete linkage, kc, is given by the rate at which favorable combinations of double mutantS are produced by compensatory mutation. For r > 0, kc, decreases exponentially with r. In contrast, kc, becomes independent of r for weak selection. We discuss the dynamics of evolutionary substitutions of compensatory mutants in relation to Wright'S shifting balance theory of evolution and use our results to analyze the substitution process in helices of mRNA secondary structures.

Ovarian and endocrine responses to prostaglandin F2α (PGF2α) given at the expected time of the endogenous FSH peak at mid-cycle in ewes

2006 ◽  
Vol 66 (4) ◽  
pp. 811-821 ◽  
Author(s):  
Xinyu Liu ◽  
Qiao Dai ◽  
Ezra J. Hart ◽  
Rajesha Duggavathi ◽  
David M.W. Barrett ◽  
...  
Keyword(s):  
Prostaglandin F2α ◽  
Expected Time
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