With the rapid development of wireless communication technology and the rapid increase in demand for network bandwidth, IEEE 802.16e is an emerging network technique that has been deployed in many metropolises. In add...
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With the rapid development of wireless communication technology and the rapid increase in demand for network bandwidth, IEEE 802.16e is an emerging network technique that has been deployed in many metropolises. In addition to the features of high data rate and large coverage, it also enables scalable video multicasting, which is a potentially promising application, over an IEEE 802.16e network. How to optimally assign the modulation and coding scheme (MCS) of the scalable video stream for the mobile subscriber stations to improve spectral efficiency and maximize utility is a crucial task. We formulate this MCS assignment problem as an optimization problem, called the total utility maximization problem (TUMP). This article transforms the TUMP into a precedence constraint knapsack problem, which is a NP-complete problem. Then, a branch and bound method, which is based on two dominance rules and a lower bound, is presented to solve the TUMP. The simulation results show that the proposed branch and bound method can find the optimal solution efficiently.
In the scheduling literature, it is often assumed that jobs arrive either simultaneously or individually. However, this assumption is invalid in most practical situations because jobs usually arrive in batches, e.g., ...
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In the scheduling literature, it is often assumed that jobs arrive either simultaneously or individually. However, this assumption is invalid in most practical situations because jobs usually arrive in batches, e.g., the final testing house in the manufacturing of semiconductor. The concept of batch arrivals has been mentioned in some studies, but it has not been explored from an operational viewpoint. This paper first addresses an identical parallel machine problem with batch arrivals to minimize the total completion time. Since the problem is NP-hard, a heuristic based on binary integer program is proposed. Computational results show that the proposed heuristic can efficiently obtain good solutions for medium and large size problems with an average percentage error of 2.12 from the lower bound. (C) 2009 Elsevier B.V. All rights reserved.
In a discrete network design problem, an optimal subset is chosen from a set of proposed link additions to an existing road network in order to minimize the total cost of users. The problem has been called as a comple...
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In a discrete network design problem, an optimal subset is chosen from a set of proposed link additions to an existing road network in order to minimize the total cost of users. The problem has been called as a complex issue in the transportation planning literature. The main source of complexity is that the problem is a bilevel program in which the lower-level program is a traffic assignment problem. In this paper, a path-based traffic assignment problem is used as the lower-level problem. The path-based algorithms not only provide the link-flow solution, but also the useful path-flow solution (path information) that may be required or used in certain applications, such as network design problem. To solve a network design problem, the traffic assignment problem will need to be solved many times. The main objective of this paper is to expedite the solution of the network design problem by initializing traffic assignment problems with path sets already found in previously performed traffic assignments. The rationale behind this idea is that the addition of a number of proposed links to a network will not change the used paths for the majority of origin-destination (OD) pairs. In this paper, the network design problem is solved by a branch and bound algorithm for a small network and a relatively large network. It is shown that the proposed method is capable of reducing the computation time to one-fifth in real-size networks. DOI: 10.1061/(ASCE)TE.1943-5436.0000389. (C) 2012 American Society of Civil Engineers.
In this paper, we consider a rescheduling problem where a set of jobs has already been assigned to unrelated parallel machines. When a disruption occurs on one of the machines, the affected jobs are rescheduled, consi...
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In this paper, we consider a rescheduling problem where a set of jobs has already been assigned to unrelated parallel machines. When a disruption occurs on one of the machines, the affected jobs are rescheduled, considering the efficiency and stability measures. Our efficiency measure is the total flow time and stability measure is the total reassignment cost caused by the differences in the machine allocations in the initial and new schedules. We propose a branch and bound algorithm to generate all efficient solutions with respect to our efficiency and stability measures. We improve the efficiency of the algorithm by incorporating powerful reduction and bounding mechanisms. Our computational tests on large sized problem instances have revealed the satisfactory behaviour of our algorithm.
In the paper, we study a flexible assembly line design problem with equipment decisions. We assume the task times and equipment costs are correlated in the sense that for all tasks the cheaper equipment gives no small...
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In the paper, we study a flexible assembly line design problem with equipment decisions. We assume the task times and equipment costs are correlated in the sense that for all tasks the cheaper equipment gives no smaller task time. Given the cycle time and number of workstations we aim to find the assignment of tasks and equipment to the workstations so as to minimise the total equipment cost. We develop a branch and bound algorithm that uses powerful lower bounds and reduction mechanisms. Our computational experiments have revealed that our algorithm can solve large-sized problem instances in reasonable solution times.
This paper studies a two-machine scheduling problem with deteriorating jobs which their processing times depend on their waiting time. We develop a branch and bound algorithm to minimize the total tardiness criteria. ...
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This paper studies a two-machine scheduling problem with deteriorating jobs which their processing times depend on their waiting time. We develop a branch and bound algorithm to minimize the total tardiness criteria. A lower bound, several dominance properties and an initial upper bound derived from a heuristic algorithm are used to increase the speed of branch and bound algorithm and decrease its required memory space. Computational results are presented to evaluate effectiveness and efficiency of the algorithms. (C) 2011 Elsevier Inc. All rights reserved.
The problem of designing jerk limited-time optimal control profiles for rest-to-rest maneuvers of flexible structures with multiple actuators is addressed. The problem formulation includes constraints to cancel the po...
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The problem of designing jerk limited-time optimal control profiles for rest-to-rest maneuvers of flexible structures with multiple actuators is addressed. The problem formulation includes constraints to cancel the poles corresponding to the rigid-body mode and flexible modes of the system and to satisfy the boundary conditions of the rest-to-rest maneuver. Further constraints can be added to increase robustness to parametric uncertainties of the plant. The technique proposed is applied to a three-mass/two-spring system and the evolution or the shape of the control profile as a function of jerk is illustrated.
Most transit agencies require government support for the replacement of their aging fleet A procedure for equitable resource allocation among competing transit agencies for the purpose of transit fleet management is p...
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Most transit agencies require government support for the replacement of their aging fleet A procedure for equitable resource allocation among competing transit agencies for the purpose of transit fleet management is presented in this study The proposed procedure is a 3-dimensional model that includes the choice of a fleet improvement program, agencies that may receive them, and the timing of investments Earlier efforts to solve this problem involved the application of 1- or 2-dimensional models for each year of the planning period These may have resulted in suboptimal solution as the models are blind to the impact of the fleet management program of the subsequent years Therefore, a new model to address a long-term planning horizon is proposed. The model is formulated as a non-linear optimization problem of maximizing the total weighted average remaining life of the fleet subjected to improvement program and budgetary constraints Two variants of the problem, one with an annual budget constraint and the other with a single budget constraint for the entire planning period, are formulated. Two independent approaches, namely, branch and bound algorithm and genetic algorithm are used to obtain the solution An example problem is solved and results are discussed in details. Finally, the model is applied to a large scale real-world problem and a detailed analysis of the results is presented. (C) 2010 Elsevier Ltd All rights reserved.
The signaling dimension of any given physical system represents its classical simulation cost, that is, the minimum dimension of a classical system capable of reproducing all the input/output correlations of the given...
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The signaling dimension of any given physical system represents its classical simulation cost, that is, the minimum dimension of a classical system capable of reproducing all the input/output correlations of the given system. The signaling dimension landscape is vastly unexplored;the only non-trivial systems whose signaling dimension is known - other than quantum systems - are the octahedron and the composition of two squares. Building on previous results by Matsumoto, Kimura, and Frenkel, our first result consists of deriving bounds on the signaling dimension of any system as a function of its Minkowski measure of asymmetry. We use such bounds to prove that the signaling dimension of any two-dimensional system (i.e. with two-dimensional set of admissible states, such as polygons and the real qubit) is two if and only if such a set is centrally symmetric, and three otherwise, thus conclusively settling the problem of the signaling dimension for such systems. Guided by the relevance of symmetries in the two dimensional case, we propose a branch and bound division-free algorithm for the exact computation of the symmetries of any given polytope, in polynomial time in the number of vertices and in factorial time in the dimension of the space. Our second result then consist of providing an algorithm for the exact computation of the signaling dimension of any given system, that outperforms previous proposals by exploiting the aforementioned bounds to improve its pruning techniques and incorporating as a subroutine the aforementioned symmetries-finding algorithm. We apply our algorithm to compute the exact value of the signaling dimension for all rational Platonic, Archimedean, and Catalan solids, and for the class of hyper-octahedral systems up to dimension five.
Multiple Traveling Salesman Problem (MTSP) is able to model and solve various real-life applications such as multiple scheduling, multiple vehicle routing and multiple path planning problems, etc. While Traveling Sale...
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Multiple Traveling Salesman Problem (MTSP) is able to model and solve various real-life applications such as multiple scheduling, multiple vehicle routing and multiple path planning problems, etc. While Traveling Salesman Problem (TSP) focuses on searching a path of minimum traveling distance to visit all cities exactly once by one salesman, the objective of the MTSP is to find m paths for m salesmen with a minimized total cost - the sum of traveling distances of all salesmen through all of the respective cities covered. They have to start from a designated depot which is the departing and returning location of all salesmen. Since the MTSP is a NP-hard problem, a new effective Genetic algorithm with Local operators (GAL) is proposed in this paper to solve the MTSP and generate high quality solution within a reasonable amount of time for real-life applications. Two new local operators, branch and bound (BaB) and Cross Elimination (CE), are designed to speed up the convergence of the search process and improve the solution quality. Results demonstrate that GAL finds a better set of paths with a 9.62% saving on average in cost comparing to two existing MTSP algorithms.
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