8 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 8 / 8
Yayın Tractable supply chain production planning, modeling nonlinear lead time and quality of service constraints(Elsevier Ltd, 2007) Anlı, Osman Murat; Caramanis, Michael C.; Paschalidis, Ioannis Ch.This paper addresses the task of coordinated planning of a supply chain (SC). Work in process (WIP) in each facility participating in the SC, finished goods inventory, and backlogged demand costs are minimized over the planning horizon. In addition to the usual modeling of linear material flow balance equations, variable lead time (LT) requirements, resulting from the increasing incremental WIP as a facility's utilization increases, are also modeled. In recognition of the emerging significance of quality of service (QoS), that is control of stockout probability to meet demand on time, maximum stockout probability constraints are also modeled explicitly. Lead time and QoS modeling require incorporation of nonlinear constraints in the production planning optimization process. The quantification of these nonlinear constraints must capture statistics of the stochastic behaviour of production facilities revealed during a time scale for shorter than the customary weekly time scale of the planning process. The apparent computational complexity of planning production against variable LT and QoS constraints has long resulted in MRP-based scheduling practices that ignore the LT and QoS constraints has long resulted in MRP-based scheduling practices that ignore the LT and QoS impact to the plan's detriment. The computational complexity challenge was overcome by proposing and adopting a time-scale decomposition approach to production planning where short-time-scale stochastic dynamics are modeled in multiple facility-specific subproblems that receive tentative targets from a deterministic master problem and return statistics to it. A converging and scalable iterative methodology is implemented, providing evidence that significantly lower cost production plans are achievable in a computationally tractable manner.Yayın Classification-based macroblock layer rate control for low delay transmission of H.263 video(IS & T - Soc Imaging Science Technology, 2003-07) Bayazıt, UluğPuri and Aravind's method of macroblock bit count estimation for video rate control is based on the classification of the macroblock data into discrete classes and assigning a unique non-linear estimate for each class and quantization parameter pair. This method stands apart from other methods in the literature, since the model of the bit count versus the quantization parameter relation, parameterized by macroblock variance, is a discrete model generated solely from measurements, We extend their technique for low-delay video rate control (tight buffer regulation) in two ways. We propose a strategy of near-uniform quantization parameter assignments to the macroblocks of a frame that can come close to maximizing an objective spatial quality function, such as PSNR, over the entire frame. We also adaptively update the quantization parameter assignments for the yet to be coded macroblocks, after the encoding of each macroblock, to compensate for any errors in the bit count estimation of the encoded macroblock. Our experiments demonstrate that the proposed rate control method can more accurately control the number of bits expended for a frame, as well as yield a higher objective spatial quality than the method adopted by TMN8.Yayın A travelling wave solution to the KdV-Burgers equation(Elsevier Inc, 2004-07-15) Demiray, HilmiIn the present work, by introducing a new potential function and by using the hyperbolic tangent method and an exponential rational function approach, a travelling wave solution to the KdV-Burgers (KdVB) equation is presented. It is observed that both methods lead to the same type of solution. The solution method we introduced here is less restrictive and comprises some solutions existing in the current literature [Wave Motion 11 (1989) 559; Wave Motion 14 (1991) 559].Yayın BinBRO: Binary Battle Royale Optimizer algorithm(Elsevier Ltd, 2022-02-04) (Rahkar Farshi), Taymaz Akan; Agahian, Saeid; Dehkharghani, RahimStochastic methods attempt to solve problems that cannot be solved by deterministic methods with reasonable time complexity. Optimization algorithms benefit from stochastic methods; however, they do not guarantee to obtain the optimal solution. Many optimization algorithms have been proposed for solving problems with continuous nature; nevertheless, they are unable to solve discrete or binary problems. Adaptation and use of continuous optimization algorithms for solving discrete problems have gained growing popularity in recent decades. In this paper, the binary version of a recently proposed optimization algorithm, Battle Royale Optimization, which we named BinBRO, has been proposed. The proposed algorithm has been applied to two benchmark datasets: the uncapacitated facility location problem, and the maximum-cut graph problem, and has been compared with 6 other binary optimization algorithms, namely, Particle Swarm Optimization, different versions of Genetic Algorithm, and different versions of Artificial Bee Colony algorithm. The BinBRO-based algorithms could rank first among those algorithms when applying on all benchmark datasets of both problems, UFLP and Max-Cut.Yayın A low complexity modulation classification algorithm for MIMO systems(IEEE-INST Electrical Electronics Engineers Inc, 2013-10) Mühlhaus, Michael S.; Öner, Mustafa Mengüç; Dobre, Octavia Adina; Jondral, Friedrich K.A novel algorithm is proposed for automatic modulation classification in multiple-input multiple-output spatial multiplexing systems, which employs fourth-order cumulants of the estimated transmit signal streams as discriminating features and a likelihood ratio test (LRT) for decision making. The asymptotic likelihood function of the estimated feature vector is analytically derived and used with the LRT. Hence, the algorithm can be considered as asymptotically optimal for the employed feature vector when the channel matrix and noise variance are known. Both the case with perfect channel knowledge and the practically more relevant case with blind channel estimation are considered. The results show that the proposed algorithm provides a good classification performance while exhibiting a significantly lower computational complexity when compared with conventional algorithms.Yayın Rate-distortion and complexity optimized motion estimation for H.264 video coding(IEEE-INST Electrical Electronics Engineers Inc, 2008-02) Ateş, Hasan Fehmi; Altunbaşak, Yücel11.264 video coding standard supports several inter-prediction coding modes that use macroblock (MB) partitions with variable block sizes. Rate-distortion (R-D) optimal selection of both the motion vectors (MVs) and the coding mode of each MB is essential for an H.264 encoder to achieve superior coding efficiency. Unfortunately, searching for optimal MVs of each possible subblock incurs a heavy computational cost. In this paper, in order to reduce the computational burden of integer-pel motion estimation (ME) without sacrificing from the coding performance, we propose a R-D and complexity joint optimization framework. Within this framework, we develop a simple method that determines for each MB which partitions are likely to be optimal. MV search is carried out for only the selected partitions, thus reducing the complexity of the ME step. The mode selection criteria is based on a measure of spatiotemporal activity within the MB. The procedure minimizes the coding loss at a given level of computational complexity either for the full video sequence or for each single frame. For the latter case, the algorithm provides a tight upper bound on the worst case complexity/execution time of the ME module. Simulation results show that the algorithm speeds up integer-pel ME by a factor of up to 40 with less than 0.2 dB loss in coding efficiency.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.Yayın Fast algorithm analysis and bit-serial architecture design for sub-pixel motion estimation in H.264(World Scientific Publishing Company, 2010-12) Fatemi, Mohammad Reza Hosseiny; Ateş, Hasan Fehmi; Salleh, Rosli BinThe sub-pixel motion estimation (SME), together with the interpolation of reference frames, is a computationally extensive part of the H.264 encoder that increases the memory requirement 16-times for each reference frame. Due to the huge computational complexity and memory requirement of the H.264 SME, its hardware architecture design is an important issue especially in high resolution or low power applications. To solve the above difficulties, we propose several optimization techniques in both algorithm and architecture levels. In the algorithm level, we propose a parabolic based algorithm for SME with quarter-pixel accuracy which reduces the computational budget by 94.35% and the memory access requirement by 98.5% in comparison to the standard interpolate and search method. In addition, a fast version of the proposed algorithm is presented that reduces the computational budget 46.28% further while maintaining the video quality. In the architecture level, we propose a novel bit-serial architecture for our algorithm. Due to advantages of the bit-serial architecture, it has a low gate count, high speed operation frequency, low density interconnection, and a reduced number of I/O pins. Also, several optimization techniques including the sum of absolute differences truncation, source sharing exploiting and power saving techniques are applied to the proposed architecture which reduce power consumption and area. Our design can save between 57.71-90.01% of area cost and improves the macroblock (MB) processing speed between 1.7-8.44 times when compared to previous designs. Implementation results show that our design can support real time HD1080 format with 20.3 k gate counts at the operation frequency of 144.9 MHz.
