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  • Economics  (3)
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  • Economics  (3)
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  • 1
    Online Resource
    Online Resource
    EDP Sciences ; 2022
    In:  RAIRO - Operations Research Vol. 56, No. 1 ( 2022-01), p. 395-414
    In: RAIRO - Operations Research, EDP Sciences, Vol. 56, No. 1 ( 2022-01), p. 395-414
    Abstract: This paper proposes an M / G /1 queueing model with bi-level randomized ( p ,  N 1 ,  N 2 )-policy. That is, after all of the customers in the system are served, the server is closed down immediately. If N 1 (≥ 1) customers are accumulated in the queue, the server is activated for service with probability p (0 ≤ p ≤ 1) or still left off with probability 1 −  p . When the number of customers in the system becomes N 2 (≥  N 1 ), the server begins serving the waiting customers until the system becomes empty again. Using the total probability decomposition technique and the Laplace transform, we study the transient queue length distribution and obtain the expressions of the Laplace transform of the transient queue-length distribution with respect to time t . Then, employing L’Hospital’s rule and some algebraic operations, the explicit recursive formulas of the steady-state queue-length distribution, which can be used to accurately evaluate the probabilities of queue length, are presented. Moreover, some other important queuing performance indices, such as the explicit expressions of its probability generating function of the steady-state queue-length distribution, the expected queue size and so on, are derived. Meanwhile, we investigate the system capacity optimization design by the steady-state queue-length distribution. Finally, an operating cost function is constructed, and by numerical calculation, we find the minimum of the long-run average cost rate and the optimal bi-level threshold policy ( N * 1 , N * 2 ) that satisfies the average waiting time constraints.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
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  • 2
    Online Resource
    Online Resource
    EDP Sciences ; 2015
    In:  RAIRO - Operations Research Vol. 49, No. 4 ( 2015-10), p. 717-734
    In: RAIRO - Operations Research, EDP Sciences, Vol. 49, No. 4 ( 2015-10), p. 717-734
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 1290-3868
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2015
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
    Location Call Number Limitation Availability
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  • 3
    Online Resource
    Online Resource
    Wiley ; 2015
    In:  International Transactions in Operational Research Vol. 22, No. 3 ( 2015-05), p. 545-562
    In: International Transactions in Operational Research, Wiley, Vol. 22, No. 3 ( 2015-05), p. 545-562
    Abstract: This paper proposes a general model for the bus route schedule design (BRSD) problem considering the uncertainty in the bus travel times to minimize the expected total schedule deviation from a reliability standpoint. The preferences of bus operators are considered in the objective function. Based on the general model, four stochastic linear programming models are subsequently developed by successively incorporating different operation strategies; they include (1) no control strategy (NCS), (2) bus drivers’ schedule recovery (DSR), (3) holding control strategy (HCS), and (4) both DSR and HCS (BRHS). Then, a Monte Carlo simulation based solution method is designed to solve these four models, respectively. Finally, numerical tests based on a real bus route are used for a comparative analysis of different operation strategies used in the BRSD. The results show that HCS and BRHS outperform other operation strategies in terms of the schedule deviation of the buses. Interestingly, HCS performs slightly better than BRHS when bus operators assume that later arrival at scheduled point is more harmful than earlier arrival. Compared to NCS, HCS can save objective function approximately 67.9% in all cases. In addition, operation strategies that could better fit a particular scenario are suggested.
    Type of Medium: Online Resource
    ISSN: 0969-6016 , 1475-3995
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2015
    detail.hit.zdb_id: 2019815-2
    SSG: 3,2
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