Desalinated water is becoming a significant resource in many countries. With limited water supply, several high-demand sites located far from the desalination plant and an efficient and cost-effective transmission and...
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Desalinated water is becoming a significant resource in many countries. With limited water supply, several high-demand sites located far from the desalination plant and an efficient and cost-effective transmission and storage network have become critical. In many areas, desalinated water is not delivered efficiently through a pipeline and storage tank system capable of providing safe and cost-effective coverage to a wide range of demand sites. In addition, due to the limitation of transmission and storage distribution, many desalination plants are unable to achieve full production capacity. Many high-demand sites are at risk of disruption or water contamination due to single-source pipelines or desalination plants. In this study, the conceptual framework for an economically viable transmission and storage system helps decision-makers to define the requirements for the proper design of the system. The definition is introduced here to describe strategic tanks for efficient and economical supply allocation. The key aspects of setting up effective transmission and storage systems were outlined in the framework presented. To develop an efficient and cost-effective transmission and storage system, an integerlinear program was constructed to solve the hub and spoke issue. A hypothetical example is presented and discussed to illustrate the advantages of the proposed model.
Heuristic mining techniques are among the most popular methods in the process discovery area. This category of methods is composed of two main steps: (1) discovering a dependency graph and (2) determining the split/jo...
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Heuristic mining techniques are among the most popular methods in the process discovery area. This category of methods is composed of two main steps: (1) discovering a dependency graph and (2) determining the split/join patterns of the dependency graph. The current dependency graph discovery techniques of heuristic-based methods select the initial set of graph arcs according to dependency measures and then modify the set regarding some criteria. This can lead to selecting the non-optimal set of arcs. Also, the modifications can result in modeling rare behaviors and, consequently, low precision and non-simple process models. The motivation of this paper is to improve the heuristic mining methods by addressing the mentioned issues. The contribution of this paper is to propose a new integer linear programming model that determines the optimal set of graph arcs regarding dependency measures. Simultaneously, the proposed method can eliminate some other issues that the existing methods cannot handle completely;i.e., even in the presence of loops, it guarantees that all tasks are on a path from the initial to the final tasks. This approach also allows utilizing domain knowledge by introducing appropriate constraints, which can be a practical advantage in real-world problems. To assess the results, we modified two existing methods of evaluating process models to make them capable of measuring the quality of dependency graphs. According to assessments, the proposed method's outputs are superior to those of the most prominent dependency graph discovery methods in terms of fitness, precision, and especially simplicity.
In this paper, we define a new subclass of integer linear programming problems called the composition problem. We shall propose efficient algorithms for solving this problem and its variants. Moreover, as an applicati...
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In this paper, we define a new subclass of integer linear programming problems called the composition problem. We shall propose efficient algorithms for solving this problem and its variants. Moreover, as an application of the composition problem, those algorithms are applied to solve the P-constrained secure set problem, which is a variation of the secure set problem introduced in [5], on trees. A P-constrained secure set problem is to find a minimum secure set containing a set of vertical bar P vertical bar predetermined vertices.
Virtualization technology allows service providers to operate data centers in a cost-effective and scalable manner. The data center network (substrate network) and the applications executed in the data center (virtual...
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Virtualization technology allows service providers to operate data centers in a cost-effective and scalable manner. The data center network (substrate network) and the applications executed in the data center (virtual networks) are often modeled as graphs. The nodes of the graphs represent (physical or virtual) servers and switches, and the edges represent communication links. Nodes and links are annotated with the provided and required resources (e.g., memory and bandwidth). The NP-hard virtual network embedding (VNE) problem deals with the embedding of a set of virtual networks to the substrate network such that (i) all (resource) constraints of the substrate network are fulfilled, and (ii) an objective is optimized (e.g., minimizing the communication costs). The existing two-step highly customizable model-driven virtual network embedding (MdVNE) approach combines model transformation (MT) and integer linear programming (ILP) techniques to solve the VNE problem based on a declarative specification. MdVNE generates element mapping candidates from an MT specification and identifies an optimal and correct embeddings using an ILP solver. In the past, developers created the MT and ILP specifications manually and needed to ensure carefully that both are compatible and respect the problem description. In this article, we present a novel construction methodology for synthesizing the MT and ILP specification from a given declarative model-based VNE problem description. This problem description consists of a metamodel for substrate and virtual networks, additional OCL constraints, and an objective function that assigns costs to a given model. This methodology ensures that the derived embeddings are correct w.r.t. the metamodel and the OCL constraints, and optimal w.r.t. the optimization goal. The novel model-based VNE specification is applicable to different network domains, environments, and constraints. Thus, the construction methodology allows to automate most of the ste
This paper considers the multi level uncapacitated facility location problem (MLUFLP). A new mixed integer linear programming (MILP) formulation is presented and validity of this formulation is given. Experimental res...
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This paper considers the multi level uncapacitated facility location problem (MLUFLP). A new mixed integer linear programming (MILP) formulation is presented and validity of this formulation is given. Experimental results are performed on instances known from literature. The results achieved by CPLEX and Gurobi solvers, based on the proposed MILP formulation, are compared to the results obtained by the same solvers on the already known formulations. The results show that CPLEX and Gurobi can optimally solve all small and medium sized instances and even some large-scale instances using the new formulation. (C) 2013 Elsevier Inc. All rights reserved.
We address the problem of planning outages of nuclear power plants submitted by EDF (A parts per thousand lectricit, De France) as the challenge EURO/ROADEF 2010. As our team won the first prize of the contest in the ...
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We address the problem of planning outages of nuclear power plants submitted by EDF (A parts per thousand lectricit, De France) as the challenge EURO/ROADEF 2010. As our team won the first prize of the contest in the senior category, our approach may be of interest: it is conceptually simple, easy to program and computationally relatively fast. We present both our method and some ideas to improve it.
A Hamiltonian decomposition of a regular graph is a partition of its edge set into Hamiltonian cycles. We consider the second Hamiltonian decomposition problem: for a 4-regular multigraph, find 2 edge-disjoint Hamilto...
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A Hamiltonian decomposition of a regular graph is a partition of its edge set into Hamiltonian cycles. We consider the second Hamiltonian decomposition problem: for a 4-regular multigraph, find 2 edge-disjoint Hamiltonian cycles different from the given ones. This problem arises in polyhedral combinatorics as a sufficient condition for non-adjacency in the 1-skeleton of the traveling salesperson polytope. We introduce two integer linear programming models for the problem based on the classical Dantzig-Fulkerson-Johnson and Miller-Tucker-Zemlin formulations for the traveling salesperson problem. To enhance the performance on feasible problems, we supplement the algorithm with a variable neighborhood descent heuristic w.r.t. two neighborhood structures and a chain edge fixing procedure. Based on the computational experiments, the Dantzig-Fulkerson-Johnson formulation showed the best results on directed multigraphs, while on undirected multigraphs, the variable neighborhood descent heuristic was especially effective.
The explosive traffic growths are pushing the transport network close to its capacity limitation, raising critical issues about fiber capacity crunch. In this context, network coding has been emerging as the promising...
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The explosive traffic growths are pushing the transport network close to its capacity limitation, raising critical issues about fiber capacity crunch. In this context, network coding has been emerging as the promising technique to improve the network capacity efficiency thanks to the capability of better resources utilization. The application of network coding to the realms of failure recovery in optical networks has paved the new way for more efficient protection schemes and indeed, XOR network coding combined with dedicated protection has been proposed, investigated and developed to challenge the well-established understanding of trading capacity efficiency for recovery speed and vice versa. In order to maximize the benefits empowered by network coding in this case, the problem of 1 + 1 routing and network coding assignment (1 + 1 RNCA) has to be optimally solved. Apart from traditional 1 + 1 routing, the decision of network coding information has also to be taken into account including the selection of pair of demands for encoding and the respective coding node and coding links. In this paper, we propose a bi-objective integer linear programming model of the 1 + 1 RNCA problem aiming at minimizing the conventional routing cost as the primary objective and furthermore minimizing the number of nodes with coding capabilities as the secondary objective. Our formulation uses a weighting method to combine two objectives into an integrated one and we provide a rigorous analysis on configuring the weight coefficients to capture the desired priority of individual objectives. The efficiency of our integrated objective model in comparison with reference designs based on the single-objective model, 1 + 1 routing and 1 + 1 RNCA, is numerically evaluated on different realistic topologies and traffic sets. Extensive simulation demonstrates that our proposal outperforms traditional approaches when it could achieve the lowest routing cost while simultaneously employing minimal nu
Home energy management system is proposed to reduce the influences caused by the high ratio penetration of renewable energy generation, through managing and dispatching the residential power and energy consumption in ...
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Home energy management system is proposed to reduce the influences caused by the high ratio penetration of renewable energy generation, through managing and dispatching the residential power and energy consumption in the demand side. Being aware of how the electric energy is consumed is a key step of this system. Non-intrusive Load Monitoring is regarded as the most potential method to address this problem, which aims to separate individual appliances in households by decomposing the total power consumption. In recent years, NILM is framed as a multi-label classification problem and many researches has been investigated in this field. In this paper, a non-intrusive method which can identify appliances power usage information from the total power consumption is proposed and thoroughly investigated. Firstly, the random k-labelset multi-label classification algorithm is enhanced by introducing random forest algorithm as base classifier. Then, grid search method and cross validation method are integrated to determine the optimal paraments set. This algorithm is used to achieve the appliances identification. Finally, based on the identification result, the integer linear programming is employed for power estimation of each appliance, especially multi-state appliances. Experimental results on low voltage networks simulator demonstrate that the proposed method has a high identification accuracy compared with the traditional random k-labelset multi-label classification methods with other base classifiers, and it is capable of identifying the power usages of different appliances accurately. The desirable performance of power estimation has broadened the applications of machine learning based non-intrusive energy monitoring. (C) 2021 The Author(s). Published by Elsevier Ltd.
This paper presents an instance of the rectangular packing problem which arises in the implementation of a graphical user interface in a windows environment. The problem consists of a single, containing rectangle of f...
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This paper presents an instance of the rectangular packing problem which arises in the implementation of a graphical user interface in a windows environment. The problem consists of a single, containing rectangle of finite dimension and an ordered collection of rectangular objects to be packed in the rectangle. The size of the containing rectangle is dynamic, and restrictions are placed on the subset of the objects that can be packed in tire rectangle at any given instance. A detailed description of the general problem is provided and a mathematical formulation is presented. A specific, real-world application is then introduced and modeled as an integer linear programming problem. Finally, due to the intractability of a direct solution of the mathematical model, a network representation of the problem is derived from which an efficient branch-and-bound solution algorithm is developed. The performance with respect to execution time of the branch-and-bound algorithm is analyzed for various instances of the problem and the quality of solution with respect to objective value is compared with that of an ad hoc method.
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