In recent years, dependency on computer networks has been increasing due to the increasing speed and capacity of data transmission. To guarantee the quality of service in networks, new technologies are being developed...
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ISBN:
(纸本)9781665431941
In recent years, dependency on computer networks has been increasing due to the increasing speed and capacity of data transmission. To guarantee the quality of service in networks, new technologies are being developed. The use of optical-channel data unit (ODU) technology in optical networks can segment and combine the required traffic demands and make effective use of network resources so that more traffic demands can be satisfied. An algorithm for addressing multiple ODU switch failures is described in this paper. This paper proposes three models to prevent multiple failures and formulates them as integer linear programming problems. The computer experiments compare their efficiencies. As a result, each traffic demand on the network is divided into plural paths, and less calculation time is required when the capacity allocated to each path is fixed. When the same method is used but the capacity allocated to each path is unfixed, the resource cost is relatively small.
This paper proposes a heuristic method for inventory optimisation of agri-fresh food products. The problem consists of multiple varieties of agri-fresh products collected in the harvest season that must be stored in a...
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ISBN:
(纸本)9781728125473
This paper proposes a heuristic method for inventory optimisation of agri-fresh food products. The problem consists of multiple varieties of agri-fresh products collected in the harvest season that must be stored in a limited number of warehouses to supply demand throughout the whole planning horizon. The warehouses can be set on two modes with different energy consumption rates and different impacts on preventing product losses. The aim is to minimise the costs of energy consumption and product loss. Based on a mixed integerlinearprogramming model for the problem, which is effective only for small instances due to the complexity of the problem, we propose an efficient two-phase heuristic method. In the first phase, a problem-specific heuristic determines and fixes the values of the binary variables, and then, in the second phase, the mixed integer linear programming problem is solved to determine the remaining variables. We evaluated the performance of the proposed approach by solving instances with different sizes. The results illustrate that the two-phase approach can efficiently find solutions of good quality.
In current environment, many web services map to the distributed data centers, to respond to variable and increasing workloads. It is not cost efficient for one data center to increase number of servers in order to fu...
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ISBN:
(纸本)9781728168234
In current environment, many web services map to the distributed data centers, to respond to variable and increasing workloads. It is not cost efficient for one data center to increase number of servers in order to fulfill all requests coming to it. For this reason, federated data center is a key solution for sharing unused resources and gain sonic profit. In this paper, we have used demand multiplexing and exploits the spatio-temporal variation of electricity price of distributed data center across locations and also consider the power consumption cost of servers at data center. We develop an integer linear programming problem (ILPP) for Profit Maximization problem of federated data centers and proposes Greedy algorithm for computing an optimal federation formation of data centers. The performance of the proposed Greedy federation formation algorithm (G-FM) compares with two other algorithms which are Optimal Federation Formation Algorithm (OEM) and Random Federation Formation Algorithm (REM). Experiments are performed on real world traffic demands at data center in which the proposed (G-EM) algorithm gives an optimize solution to the optimization problem.
The problem of finding an optimal location of the vertices of a tree network in an assembly space representing a finite set is considered. The optimality criterion is the minimum total cost of location and communicati...
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The problem of finding an optimal location of the vertices of a tree network in an assembly space representing a finite set is considered. The optimality criterion is the minimum total cost of location and communications in all points of this space. Different vertices of the tree can be located in a single point of the assembly space. This problem is well-known as the Weber problem. The representation of the Weber problem as a linearprogrammingproblem is given. It is proved that the set of all optimal solutions to the corresponding relaxed Weber problem for the tree network contains an integer solution. This fact can be used to improve the efficiency of algorithms for the problems differing from the Weber problem by the presence of additional constraints: it allows us to find the optimal value of the objective function, which in turn significantly reduces the complexity of calculating the optimal solution itself, e.g., by the branch-and-bound method.
A pattern synthesis technique for real and coupled antenna arrays by using digital phase-only excitation weights is introduced here. The method is formulated as an integer linear programming problem incorporating a fa...
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A pattern synthesis technique for real and coupled antenna arrays by using digital phase-only excitation weights is introduced here. The method is formulated as an integer linear programming problem incorporating a fast full-wave analysis of the array, based on the finite element method and spherical mode expansions. The method achieves radiation patterns with specified pointing directions, main lobe widths, minimum sidelobe level, and prescribed nulls, controlled by digital phase shifters.
A new heuristic method is proposed for the problem of vessel routing optimisation for offshore wind farms. Turbines requiring a maintenance action are arranged into clusters, each associated with a vessel and a value ...
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A new heuristic method is proposed for the problem of vessel routing optimisation for offshore wind farms. Turbines requiring a maintenance action are arranged into clusters, each associated with a vessel and a value for repairing the turbines. The clusters with the highest value are used to produce offspring, which is selected from the remaining high-value clusters, provided the constraints are met. The process is repeated until vessels available or turbines requiring maintenance are exhausted. To test the performance of the proposed approach, the same problem was formulated as integer linear programming problem and benchmarked against the IBM CPLEX commercial solver. The proposed method was shown to consistently produce close-to-optimal policies within seconds, even in problems with 15–20 turbines requiring a maintenance action. Although the proposed method only outperformed the commercial solver in one instance, its benefits include short and consistent computational times and the fact that the users can easily understand, implement and adapt the algorithm to suit their needs.
Background: RNA-Seq based transcriptome assembly has become a fundamental technique for studying expressed mRNAs (i.e., transcripts or isoforms) in a cell using high-throughput sequencing technologies, and is serving ...
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Background: RNA-Seq based transcriptome assembly has become a fundamental technique for studying expressed mRNAs (i.e., transcripts or isoforms) in a cell using high-throughput sequencing technologies, and is serving as a basis to analyze the structural and quantitative differences of expressed isoforms between samples. However, the current transcriptome assembly algorithms are not specifically designed to handle large amounts of errors that are inherent in real RNA-Seq datasets, especially those involving multiple samples, making downstream differential analysis applications difficult. On the other hand, multiple sample RNA-Seq datasets may provide more information than single sample datasets that can be utilized to improve the performance of transcriptome assembly and abundance estimation, but such information remains overlooked by the existing assembly tools. Results: We formulate a computational framework of transcriptome assembly that is capable of handling noisy RNA-Seq reads and multiple sample RNA-Seq datasets efficiently. We show that finding an optimal solution under this framework is an NP-hard problem. Instead, we develop an efficient heuristic algorithm, called Iterative Shortest Path (ISP), based on linearprogramming (LP) and integerlinearprogramming (ILP). Our preliminary experimental results on both simulated and real datasets and comparison with the existing assembly tools demonstrate that (i) the ISP algorithm is able to assemble transcriptomes with a greatly increased precision while keeping the same level of sensitivity, especially when many samples are involved, and (ii) its assembly results help improve downstream differential analysis.
To date, research on the supervisor design for flexible manufacturing systems focuses on speeding up the computation of optimal (maximally permissive) liveness-enforcing controllers. Recent deadlock prevention policie...
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To date, research on the supervisor design for flexible manufacturing systems focuses on speeding up the computation of optimal (maximally permissive) liveness-enforcing controllers. Recent deadlock prevention policies for systems of simple sequential processes with resources ((SPR)-P-3) reduce the computation burden by considering only the minimal portion of all first-met bad markings (FBMs). Maximal permissiveness is ensured by not forbidding any live state. This paper proposes a method to further reduce the size of minimal set of FBMs to efficiently solve integer linear programming problems while maintaining maximal permissiveness using a vector-covering approach. This paper improves the previous work and achieves the simplest structure with the minimal number of monitors.
In this paper we focus on the use of power optimization for maximizing the network lifetime of wireless sensor networks. The goal of this paper is to improve on the algorithm suggested by Cardei et al. for solving the...
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ISBN:
(纸本)9781479974986
In this paper we focus on the use of power optimization for maximizing the network lifetime of wireless sensor networks. The goal of this paper is to improve on the algorithm suggested by Cardei et al. for solving the adjustable range set cover problem. We suggest applying the technique of Lagrangian relaxation to the integer linear programming problem formulated by Cardei et al. and using the dual variables obtained from solving the relaxed linear program as the initial values of the Lagrangian multipliers. The results of using the proposed algorithm on small examples are then compared to the results of using the methods suggested by Cardei et al. on the same examples.
Cognitive radio networks (CRN) has been depicted as one of the most important driving forces in achieving next generation wireless communication capabilities. To this end, several works are being done in describing an...
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ISBN:
(纸本)9781479974986
Cognitive radio networks (CRN) has been depicted as one of the most important driving forces in achieving next generation wireless communication capabilities. To this end, several works are being done in describing and designing this new wireless communication paradigm. In this work, a study on how dynamic resource allocation can be used in achieving the desired quality of service (QoS) in a heterogeneous CRN environment is carried out. An underlay CRN model is developed where, in the resource allocation formulation, the demands of secondary users differ but must be met concomitantly. The objective is to maximize the weighted data rate of the different categories of users in the CRN, and by so doing, achieve some required QoS. The developed problem is both non-linear and also non-deterministic polynomial-time (NP) hard. However, the problem is smartly re-formulated as an integer linear programming problem and the branch-and-bound approach is employed in obtaining optimal solutions. The QoS metrics evaluated are average data rate, throughput and outage probability. The results obtained show that optimal solutions with QoS satisfaction are achievable for the heterogeneous CRN.
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