There are significant challenges related to contamination detection and characterization within large water distribution systems. Given current sensing technology and resources, source inversion algorithms will need t...
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There are significant challenges related to contamination detection and characterization within large water distribution systems. Given current sensing technology and resources, source inversion algorithms will need to rely on manual grab samples providing only a discrete positive/negative indication of the presence of contaminant. We propose an integrated real-time strategy that identifies the set of likely locations and performs additional sampling cycles to accurately identify the contamination source. We present an MILP formulation that solves the source inversion problem using discrete (positive/negative) measurements from sparse manual grab samples at limited points in time and space. The water quality model is formulated using the origin-tracking approach and is then exactly and efficiently reduced prior to the formulation of the MILP, giving a much smaller problem that is solvable in real-time settings. The formulation is tested on a water network model comprised of over 10,000 nodes and more than 150 timesteps. (C) 2011 Elsevier Ltd. All rights reserved.
Today the most important concern of the managers is to make their firms viable in the competitive trade world. Managers are looking for effective tools for decision making in the complex business world. This paper pre...
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Today the most important concern of the managers is to make their firms viable in the competitive trade world. Managers are looking for effective tools for decision making in the complex business world. This paper presents a new mathematical model for strategic and tactical planning in a multiple-echelon, multiple-commodity production-distribution network. In the proposed model, different time resolutions are considered for strategic and tactical decisions. Also expansion of the network is planned based on cumulative net incomes. To illustrate applications of the proposed model as well as its performance based on the solution times, some hypothetical numerical examples have been generated and solved by CPLEX. Results show that in small and medium scale of instances, high quality solutions can be obtained using this solver, but for larger instances, some heuristics has to be designed to reduce solution time. (C) 2011 Elsevier Inc. All rights reserved.
In this paper the problem of finding the sparsest (i.e., minimum cardinality) critical k-tuple including one arbitrarily specified measurement is considered. The solution to this problem can be used to identify weak p...
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In this paper the problem of finding the sparsest (i.e., minimum cardinality) critical k-tuple including one arbitrarily specified measurement is considered. The solution to this problem can be used to identify weak points in the measurement set, or aid the placement of new meters. The critical k-tuple problem is a combinatorial generalization of the critical measurement calculation problem. Using topological network observability results, this paper proposes an efficient and accurate approximate solution procedure for the considered problem based on solving a minimum-cut (Min-Cut) problem and enumerating all its optimal solutions. It is also shown that the sparsest critical k-tuple problem can be formulated as a mixed integer linear programming (MILP) problem. This MILP problem can be solved exactly using available solvers such as CPLEX and Gurobi. A detailed numerical study is presented to evaluate the efficiency and the accuracy of the proposed Min-Cut and MILP calculations.
A Location-Routing Problem (LRP) combines two difficult problems, facility location and vehicle routing, and as such it is inherently hard to solve. In this paper, we propose a different formulation approach than the ...
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A Location-Routing Problem (LRP) combines two difficult problems, facility location and vehicle routing, and as such it is inherently hard to solve. In this paper, we propose a different formulation approach than the common arc-based product-flow (Arc-BPF) approach in the literature. We associate product amounts to the nodes of the network resulting in a node-based product-flow (Node-BPF) formulation. Our main objective is to develop LRP models with fewer constraints and variables, which can be solved more efficiently. To introduce the proposed approach, we reformulate a complex four-index Arc-BPF LRP model from the literature as a three-index Node-BPF model, which computationally outperforms the former. We then introduce a heuristic method.
This paper proposes a formulation of the global energy management problem of dwellings, which consists in a dynamic predictive control system able to generate optimized controls taking into account the model of the co...
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This paper proposes a formulation of the global energy management problem of dwellings, which consists in a dynamic predictive control system able to generate optimized controls taking into account the model of the concerned dwellings, i.e. homes or offices. It focuses on the adjustment of the electric energy consumption and production in order to maximize energy usage efficiency, which is seen as a compromise between energy cost and overall comfort. To reach this objective, the concept of service is introduced: basically, a service participates to the comfort and may consume energy. The available flexibilities of the services provided by domestic appliances are used to compute anticipative optimal plans for appliance controls based on a mixed integer linear programming (MILP) algorithm. A reactive mechanism based on a list algorithm is added to face unforeseen events. The paper focuses on the computation of the anticipative plans. Different MILP models of common services are proposed. Application examples are given. (C) 2011 Elsevier B.V. All rights reserved.
This paper proposes a new heuristic method for the logistics network design and planning problem based on linear relaxation and DC (difference of convex functions) programming. We consider a multi-period, multi-echelo...
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This paper proposes a new heuristic method for the logistics network design and planning problem based on linear relaxation and DC (difference of convex functions) programming. We consider a multi-period, multi-echelon, multi-commodity and multi-product problem defined as a large scale mixed integer linear programming (MILP) model. The method is experimented on data sets of various size. The numerical results validate the efficiency of the heuristic for instances with up to several dozens facilities, 18 products and 270 retailers. (C) 2010 Elsevier B.V. All rights reserved.
Modelling the effect of valve point loadings on the performance and cost of power generators for electricity dispatch problems is necessary. For the past 20 years, the development of computer based methods for the ide...
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Modelling the effect of valve point loadings on the performance and cost of power generators for electricity dispatch problems is necessary. For the past 20 years, the development of computer based methods for the identification of optimal designs have been based on a single model, introduced by Walters and Sheble (1993)[1]. This model approximates the non-monotonic incremental cost curve using a sine function. This note explores the properties of this model, highlighting one critical deficiency for use within an automated optimization based design system and proposes a new model. (C) 2011 Elsevier Ltd. All rights reserved.
This paper introduces an original planning model which integrates production, human resources and cash management decisions, taking into account the consequences that decisions in one area may have on other areas and ...
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This paper introduces an original planning model which integrates production, human resources and cash management decisions, taking into account the consequences that decisions in one area may have on other areas and allowing all these areas to be coordinated. The most relevant characteristics of the planning problem are: (1) production capacity is a non-linear function of the size of the staff;(2) firing costs may depend on the worker who is fired;(3) working time is managed under a working time account (WA) scheme, so positive balances must be paid to workers who leave the company;(4) there is a learning period for hired workers;and (5) cash management is included. A mixedintegerlinear program is designed to solve the problem. Despite the size and complexity of the model, it can be solved in a reasonable time. A numerical example, the main results of a computational experiment and a sensibility analysis illustrate the performance and benefits of the model. (C) 2011 Elsevier B.V. All rights reserved.
In this paper we propose a new heuristic framework, called Kernel Search, to solve the complex problem of portfolio selection with real features. The method is based on the identification of a restricted set of promis...
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In this paper we propose a new heuristic framework, called Kernel Search, to solve the complex problem of portfolio selection with real features. The method is based on the identification of a restricted set of promising securities (kernel) and on the exact solution of the MILP problem on this set. The continuous relaxation of the problem solved on the complete set of available securities is used to identify the initial kernel and a sequence of integer problems are then solved to identify further securities to insert into the kernel. We analyze the behavior of several heuristic algorithms as implementations of the Kernel Search framework for the solution of the analyzed problem. The proposed heuristics are very effective and quite efficient. The Kernel Search has the advantage of being general and thus easily applicable to a variety of combinatorial problems.
One of the main services of National Statistical Agencies (NSAs) for the current Information Society is the dissemination of large amounts of tabular data, which is obtained from microdata by crossing one or more cate...
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One of the main services of National Statistical Agencies (NSAs) for the current Information Society is the dissemination of large amounts of tabular data, which is obtained from microdata by crossing one or more categorical variables. NSAs must guarantee that no confidential individual information can be obtained from the released tabular data. Several statistical disclosure control methods are available for this purpose. These methods result in large linear, mixedintegerlinear, or quadratic mixedintegerlinear optimization problems. This paper reviews some of the existing approaches, with an emphasis on two of them: cell suppression problem (CSP) and controlled tabular adjustment (CTA). CSP and CTA have concentrated most of the recent research in the tabular data protection field. The particular focus of this work is on methods and results of practical interest for end-users (mostly, NSAs). Therefore, in addition to the resulting optimization models and solution approaches, computational results comparing the main optimization techniques - both optimal and heuristic - using real-world instances are also presented. (C) 2011 Elsevier B.V. All rights reserved.
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