Residential HVAC control is a large untapped resource for providing regulation services to the grid. This paper presents a set of algorithms for controlling HVACs of a group of residential houses that a demand respons...
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Residential HVAC control is a large untapped resource for providing regulation services to the grid. This paper presents a set of algorithms for controlling HVACs of a group of residential houses that a demand response aggregator can use to sell regulation service in the wholesale market. The focus is on the regulation market offered by the PJM RTO. Real-world regulation signals from PJM are used to simulate the performance and range of regulation services in a realistic scenario. After presenting the empirical counter example for why a universal optimal control strategy cannot exist for regulation, a set of heuristic algorithms is presented, which performs well in a range of test cases. The control mechanism involves a central controller communicating with smart thermostats of multiple residential houses to gather indoor temperature data, prioritizing them according to certain heuristics and sending on/off signals back to the thermostats to control the HVAC. The case studies indicate that the proposed heuristic algorithms can deliver the required regulation services, while adequately handling communication delays, different types of regulation signals and household's thermal comfort requirements.
The Three-Dimensional Bin Packing Problem (3BP) consists of allocating, without overlapping, a given set of three-dimensional rectangular items to the minimum number of three-dimensional identical finite bins. The pro...
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The Three-Dimensional Bin Packing Problem (3BP) consists of allocating, without overlapping, a given set of three-dimensional rectangular items to the minimum number of three-dimensional identical finite bins. The problem is NP-hard in the strong sense, and finds many industrial applications. We introduce a Tabu Search framework exploiting a new constructive heuristic for the evaluation of the neighborhood. Extensive computational results on standard benchmark instances show the effectiveness of the approach with respect to exact and heuristic algorithms from the literature. (C) 2002 Elsevier Science B.V. All rights reserved.
In the 2-period Travelling Salesman Problem some nodes called double nodes are visited in both of two periods while the remaining ones called single nodes are visited in either one of the periods In this paper we stud...
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In the 2-period Travelling Salesman Problem some nodes called double nodes are visited in both of two periods while the remaining ones called single nodes are visited in either one of the periods In this paper we study the case in which a balance constraint is also introduced We require that the difference between the number of visited nodes in the two periods must be below a fixed threshold Moreover we suppose that distances between nodes are Euclidean The problem is NP-hard and exact methods now available appear inadequate Here we propose three heuristics Computational experiences and a comparison between the algorithms are also given (C) 2010 Elsevier B V All rights reserved
We design heuristic algorithms to construct Hadamard matrices with two circulant cores. This hard combinatorial problem can be formulated in terms of objective functions of several binary variables, so that heuristic ...
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We design heuristic algorithms to construct Hadamard matrices with two circulant cores. This hard combinatorial problem can be formulated in terms of objective functions of several binary variables, so that heuristic methodologies can be used. Our algorithms are based on local and tabu search and they use information on the geometry of the objective function landscapes. In addition, we use the supplementary difference sets formalism to detect when solutions of a special structure exist. Using these algorithms we have computed at least one Hadamard matrix with two circulant cores of the sixteen orders 56,60,64,68,72,76,80,84,88, 92,96,100,104,108,112,116. In particular, the Hadamard matrix with two circulant cores of order 116 is constructed here for the first time, indeed it was accidentally reported as known in an earlier paper. (C) 2008 Elsevier B.V. All rights reserved.
Systematic approaches to efficient reserve network design often make use of one of two types of site selection algorithm;linear programs or heuristic algorithms. Unlike with linear programs, heuristic algorithms have ...
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Systematic approaches to efficient reserve network design often make use of one of two types of site selection algorithm;linear programs or heuristic algorithms. Unlike with linear programs, heuristic algorithms have been demonstrated to yield suboptimal networks in that more sites are selected in order to meet conservation goals than may be necessary or fewer features are captured than is possible. Although the degree of suboptimality is not known when using heuristics, some researchers have suggested that it is not significant in most cases and that heuristics are preferred since they are more flexible and can yield a solution more quickly. Using eight binary datasets, we demonstrate that suboptimality of numbers of sites selected and biodiversity features protected can occur to various degrees depending on the dataset, the model design, and the type of heuristic applied, and that processing time is not dramatically different between optimal and heuristic algorithms. In choosing an algorithm, the degree of suboptimality may not always be as important to planners as the perception that optimal solvers have feasibility issues, and therefore heuristic algorithms might continue to be a popular tool for conservation planning. We conclude that for many datasets, feasibility of optimal algorithms should not be a concern and that the value of heuristic results can be greatly improved by using optimal algorithms to determine the degree of suboptimality of the results. (C) 2007 Elsevier Ltd. All rights reserved.
Wavelength Division Multiplexing (WDM) is an important technique to make use of the large amount of bandwidths in optical fibers to meet the bandwidth requirements of applications. In this paper, two new models (MWDCR...
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Wavelength Division Multiplexing (WDM) is an important technique to make use of the large amount of bandwidths in optical fibers to meet the bandwidth requirements of applications. In this paper, two new models (MWDCRP and MCRP) of multicast routing on WDM networks are studied. In these models, it is assumed that each switch on WDM network can perform 'drop,' 'continue' and 'drop and continue' operations. In MWDCRP, given the multicast request and the delay constraint, the goal is to find a minimal wavelength light-forest to route the multicast request under the delay constraint. In MCRP, the objective cost of the multicast routing problem has two components: one is the transmitting cost, the other is the number of used wavelengths. Given the WDM network and the multicast request, the goal is to find a minimal cost light-forest to route the multicast request. Since these problems are NP-hard, four heuristic algorithms (named as Maximal-Delay-First (MDF), miNimal-Delay-First (NDF), Farthest-Greedy (FG), and Nearest-Greedy (NG)) are proposed to solve these problems. Simulation results demonstrate that the proposed algorithms can generate good solutions.
We examine the problem of broadcasting in a point-to-point computer network where a message, originated by one node, is transmitted to all nodes, subject to the restriction that an informed node can call only one of i...
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We examine the problem of broadcasting in a point-to-point computer network where a message, originated by one node, is transmitted to all nodes, subject to the restriction that an informed node can call only one of its neighbors Auring a given time unit. A dynamic programming formulation for optimal broadcasting in general networks is given, and an exact algorithm based on it is developed. Since this algorithm is not very efficient for larger networks, we present a number of heuristics for achieving efficient near-optimal algorithms. In particular, we discuss in detail a class of heuristics which require finding at each step a least-weight maximum matching in a bipartite graph.
We consider the NP-hard Multiple Depot Vehicle Scheduling Problem, in which a given set of time-tabled trips have to be assigned to vehicles stationed at different depots, so as to minimize the number of vehicles used...
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We consider the NP-hard Multiple Depot Vehicle Scheduling Problem, in which a given set of time-tabled trips have to be assigned to vehicles stationed at different depots, so as to minimize the number of vehicles used and the overall operational cost. The problem arises in the management of transportation companies In this paper some structural properties of the problem are studied and used to design a new polynomial-time heuristic algorithm which always guarantees the use of the minimum number of vehicles. Several effective refining procedures are also proposed. Extensive computational results on test problems involving up to 1,000 trips and 10 depots are reported, showing that the new approach always produces very tight approximate solutions in small computing times and outperforms other heuristics from the literature.
A dominating set in a graph G is a subset S ⊆ V(G) such that each vertex in V(G) \ S is adjacent to some vertex in S. The domination number γ(G) of G is the minimum size of a dominating set of G. The domination numbe...
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We discuss the two-machine job shop scheduling problem with availability constraints on one machine for maximum completion time (makespan) minimization. We consider the problem when unavailability periods are planned ...
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