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Yayın Optimal and near-optimal partner selection algorithms in cooperative OFDMA(IEEE, 2012) Bakşi, Saygın; Kaya, Onur; Bıyıkoğlu, TürkerWe obtain the jointly optimal power allocation and partner selection policies, that maximize the sum rate of a cooperative OFDMA system with mutually cooperating pairs of users. We show that the power allocation and partner selection steps can be performed sequentially, and the latter step can be formulated as a maximum weighted matching problem on an undirected graph, which can be solved in polynomial time. We further propose practical algorithms, and compare their performances to the optimal matching algorithm, and demonstrate that very simple and low complexity algorithms based on user-user and user-receiver distances may provide near-optimum rate performance. Moreover, we observe that algorithms that achieve superior sum-rate performance, surprisingly pair the cell edge users, with the strong users near the base station.Yayın Minimization of rest mismatches in round robin tournaments(Pergamon-Elsevier Science Ltd, 2018-11-01) Atan, Sabri Tankut; Çavdaroğlu, BurakIn sports tournaments, an occurrence of a difference in the rest periods of opponent teams in a game, which we refer to as a rest mismatch, will disadvantage the less rested team. Thus, it is only fair to expect opposing teams to have rested equally before their game. In this work, we introduce and study the Rest Mismatch Problem where the goal is to minimize the number of rest mismatches in a round robin tournament. Two integer linear formulations and a constraint programming formulation are provided, and their computational performances are compared for several problem instances. Moreover, a heuristic algorithm is developed which finds a single round robin schedule with zero mismatches when the number of teams in the tournament is a multiple of 8, and four mismatches when it is a multiple of 4 but not 8.Yayın Searching for the optimal ordering of classes in rule induction(IEEE, 2012-11-15) Ata, Sezin; Yıldız, Olcay TanerRule induction algorithms such as Ripper, solve a K > 2 class problem by converting it into a sequence of K - 1 two-class problems. As a usual heuristic, the classes are fed into the algorithm in the order of increasing prior probabilities. In this paper, we propose two algorithms to improve this heuristic. The first algorithm starts with the ordering the heuristic provides and searches for better orderings by swapping consecutive classes. The second algorithm transforms the ordering search problem into an optimization problem and uses the solution of the optimization problem to extract the optimal ordering. We compared our algorithms with the original Ripper on 8 datasets from UCI repository [2]. Simulation results show that our algorithms produce rulesets that are significantly better than those produced by Ripper proper.Yayın Energy load balancing for fixed clustering in wireless sensor networks(IEEE, 2012-05-07) Ali, Syed Amjad; Sevgi, CüneytClustering can be used as an effective technique to achieve both energy load balancing and an extended lifetime for a wireless sensor network (WSN). This paper presents a novel approach that first creates energy balanced fixed/static clusters, and then, to attain energy load balancing within each fixed cluster, rotates the role of cluster head through uniformly quantized energy levels based approach to prolong the overall network lifetime. The method provided herein, not only provides near-dynamic clustering performance but also reduces the complexity due to the fact that cluster formation phase is implemented once. The presented simulation results clearly show the efficacy of this proposed algorithm and thus, it can be used as a practical approach to obtain maximized network lifetime for energy balanced clusters in fixed clustering environments.Yayın Crossing minimization in weighted bipartite graphs(Springer, 2007) Çakıroğlu, Olca Arda; Erten, Cesim; Karataş, Ömer; Sözdinler, MelihGiven a bipartite graph G = (L-0, L-1, E) and a fixed ordering of the nodes in L-0, the problem of finding an ordering of the nodes in L-1 that minimizes the number of crossings has received much attention in literature. The problem is NP-complete in general and several practically efficient heuristics and polynomial-time algorithms with a constant approximation ratio have been suggested. We generalize the problem and consider the version where the edges have nonnegative weights. Although this problem is more general and finds specific applications in automatic graph layout problems similar to those of the unweighted case, it has not received as much attention. We provide a new technique that efficiently approximates a solution to this more general problem within a constant approximation ratio of 3. In addition we provide appropriate generalizations of some common heuristics usually employed for the unweighted case and compare their performances.Yayın Optimal project duration for resource leveling(Elsevier Science BV, 2018-04-16) Atan, Sabri Tankut; Eren, ElifResource leveling is important in project management as resource fluctuations are costly and undesired. Typically, schedules with better resource profiles are obtained by shifting the activities within their float times using the schedule of fixed duration found by Critical Path Method. However, if the project duration can be extended, it is plausible to find a schedule with enhanced resource leveling since a longer duration allows for more float time for all activities. In this work, we relax the assumption of fixed durations in resource leveling formulations and investigate what the minimal project duration for the best leveled schedule should be. We provide mixed-integer linear models for several leveling objectives including the Release and Rehire metric. We show that not all metrics used for leveling under fixed durations may be appropriate when the project duration becomes a decision variable. Optimal solutions from smaller problems are used to find the magnitude of the extension needed and benefits obtained thereby. Since the problem is a NP-hard problem for which exact solutions cannot be obtained for large networks in reasonable time, we provide a greedy heuristic to be used with the Release and Rehire metric. Using an iterative framework, we also test the performance of a state-of-the-art heuristic algorithm from the literature on our problem. Computational experiments indicate that the more the number of resources is increased, the less leveling benefits are gained from extending the project. The optimal project durations and extension benefits can also be significantly different for different metrics.
