Browsing by Subject "Computational experiment"
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Item Open Access Auction based scheduling for distributed systems(International Institute of Informatics and Systemics, 2006) Zarifoğlu, Emrah; Sabuncuoğlu, İhsanBusinesses deal with huge databases over a geographically distributed supply network. When this is combined with scheduling and planning needs, it becomes too difficult to handle. Recently, Fast Consumer Goods sector tends to consolidate their manufacturing facilities on a single supplier serving to a distributed customer network. This decentralized structure causes imperfect information sharing between customers and the supplier. We model this problem as a single machine distributed scheduling problem with job agents representing the customers and the machine agent representing the supplier. We developed Auction Based Algorithm by exploiting the opportunity to use game theoretic approach to solve the problem in the decentralized utility case. Results of our extensive computational experiments indicate that Auction Based Algorithm converges to the upper bound found for the total utility measure.Item Open Access Regenerator location problem and survivable extensions: a hub covering location perspective(Elsevier, 2015) Yıldız, B.; Karaşan, O. E.In a telecommunications network the reach of an optical signal is the maximum distance it can traverse before its quality degrades. Regenerators are devices to extend the optical reach. The regenerator placement problem seeks to place the minimum number of regenerators in an optical network so as to facilitate the communication of a signal between any node pair. In this study, the Regenerator Location Problem is revisited from the hub location perspective directing our focus to applications arising in transportation settings. Two new dimensions involving the challenges of survivability are introduced to the problem. Under partial survivability, our designs hedge against failures in the regeneration equipment only, whereas under full survivability failures on any of the network nodes are accounted for by the utilization of extra regeneration equipment. All three variations of the problem are studied in a unifying framework involving the introduction of individual flow-based compact formulations as well as cut formulations and the implementation of branch and cut algorithms based on the cut formulations. Extensive computational experiments are conducted in order to evaluate the performance of the proposed solution methodologies and to gain insights from realistic instances.Item Open Access Robust scheduling and robustness measures for the discrete time/cost trade-off problem(Elsevier, 2010) Hazır, O.; Haouari, M.; Erel, E.Projects are often subject to various sources of uncertainties that have a negative impact on activity durations and costs. Therefore, it is crucial to develop effective approaches to generate robust project schedules that are less vulnerable to disruptions caused by uncontrollable factors. In this paper, we investigate the robust discrete time/cost trade-off problem, which is a multi-mode project scheduling problem with important practical relevance. We introduce surrogate measures that aim at providing an accurate estimate of the schedule robustness. The pertinence of each proposed measure is assessed through computational experiments. Using the insights revealed by the computational study, we propose a two-stage robust scheduling algorithm. Finally, we provide evidence that the proposed approach can be extended to solve a complex robust problem with tardiness penalties and earliness revenues. © 2010 Elsevier B.V. All rights reserved.Item Open Access Time constrained maximal covering salesman problem with weighted demands and partial coverage(Elsevier Ltd, 2016) Ozbaygin, G.; Yaman, H.; Karasan, O. E.In a routing framework, it may not be viable to visit every single customer separately due to resource limitations or efficiency concerns. In such cases, utilizing the notion of coverage; i.e., satisfying the demand of multiple customers by visiting a single customer location, may be advantageous. With this motivation, we study the time constrained maximal covering salesman problem (TCMCSP) in which the aim is to find a tour visiting a subset of customers so that the amount of demand covered within a limited time is maximized. We provide flow and cut formulations and derive valid inequalities. Since the connectivity constraints and the proposed valid inequalities are exponential in the size of the problem, we devise different branch-and-cut schemes. Computational experiments performed on a set of problem instances demonstrate the effectiveness of the proposed valid inequalities in terms of strengthening the linear relaxation bounds as well as speeding up the solution procedure. Moreover, the results indicate the superiority of using a branch-and-cut methodology over a flow-based formulation. Finally, we discuss the relation between the problem parameters and the structure of optimal solutions based on the results of our experiments. © 2016 Elsevier Ltd