# Publications (until June 30, 2015)

**2015** (1)

Corinna Hallmann, Leena Suhl:

In

[Show Abstract]

**Optimizing Water Tanks in Water Distribution Systems by combining Network Reduction, Mathematical Optimization and Hydraulic Simulation**In

*OR Spectrum*, pp. 1-19. Springer**(2015)**[Show Abstract]

In the last two decades, water consumption in Germany has been decreasing, which causes the water tanks and pipes in water distribution systems to work inefficiently. This paper proposes a method that supports the planning process for tanks in water distribution systems. The method uses a combination of network reduction, mathematical optimization and hydraulic simulation. The mathematical optimization model is a non-convex Mixed Integer Quadratically Constrained Program (MIQCP) that is solved by a piecewise linearization. As this may lead to many binary variables and therefore high computing times, the size of the water distribution system model is reduced before building the optimization model. After applying several network reduction techniques and using a piecewise approximation of the original model, there may be some hydraulic differences between the original network model and the reduced network model. To make sure that the solution obtained in the optimization process is feasible in the original water distribution system model, the solution is verified by a hydraulic simulation. If the solution is not feasible, the reduced model has to be modified and solved again until the hydraulic simulation verifies a solution as feasible. In this paper, each of these processes is described and the results indicate the usefulness of each of them.

[Show BibTeX] @article{HallSuhl2014,

author = {Corinna Hallmann AND Leena Suhl},

title = {Optimizing Water Tanks in Water Distribution Systems by combining Network Reduction, Mathematical Optimization and Hydraulic Simulation},

journal = {OR Spectrum},

year = {2015},

pages = {1-19},

abstract = {In the last two decades, water consumption in Germany has been decreasing, which causes the water tanks and pipes in water distribution systems to work inefficiently. This paper proposes a method that supports the planning process for tanks in water distribution systems. The method uses a combination of network reduction, mathematical optimization and hydraulic simulation. The mathematical optimization model is a non-convex Mixed Integer Quadratically Constrained Program (MIQCP) that is solved by a piecewise linearization. As this may lead to many binary variables and therefore high computing times, the size of the water distribution system model is reduced before building the optimization model. After applying several network reduction techniques and using a piecewise approximation of the original model, there may be some hydraulic differences between the original network model and the reduced network model. To make sure that the solution obtained in the optimization process is feasible in the original water distribution system model, the solution is verified by a hydraulic simulation. If the solution is not feasible, the reduced model has to be modified and solved again until the hydraulic simulation verifies a solution as feasible. In this paper, each of these processes is described and the results indicate the usefulness of each of them.}

}

[DOI]
author = {Corinna Hallmann AND Leena Suhl},

title = {Optimizing Water Tanks in Water Distribution Systems by combining Network Reduction, Mathematical Optimization and Hydraulic Simulation},

journal = {OR Spectrum},

year = {2015},

pages = {1-19},

abstract = {In the last two decades, water consumption in Germany has been decreasing, which causes the water tanks and pipes in water distribution systems to work inefficiently. This paper proposes a method that supports the planning process for tanks in water distribution systems. The method uses a combination of network reduction, mathematical optimization and hydraulic simulation. The mathematical optimization model is a non-convex Mixed Integer Quadratically Constrained Program (MIQCP) that is solved by a piecewise linearization. As this may lead to many binary variables and therefore high computing times, the size of the water distribution system model is reduced before building the optimization model. After applying several network reduction techniques and using a piecewise approximation of the original model, there may be some hydraulic differences between the original network model and the reduced network model. To make sure that the solution obtained in the optimization process is feasible in the original water distribution system model, the solution is verified by a hydraulic simulation. If the solution is not feasible, the reduced model has to be modified and solved again until the hydraulic simulation verifies a solution as feasible. In this paper, each of these processes is described and the results indicate the usefulness of each of them.}

}

**2014** (2)

Florian Stapel, Leena Suhl:

Techreport UPB.

[Show Abstract]

**Ontology-based Representation of Optimization Models**Techreport UPB.

**(2014)**[Show Abstract]

This article presents a new approach for representing and processing abstract optimization models. Confronted with model and data integration tasks for distributed Decision Support Systems which are especially composed out of software services, we describe model constituents such as constraints both structurally and semantically. Within our approach, typed model constituents can be integrated into complete models and the instantiation of model constituents itself with data and data models can be wrapped into semantic software services. Besides others, this supports the automated generation of adaptors and the search for and composition of services. The basic idea of our approach is to represent the optimization models as instance knowledge of diﬀerent ontologies for both optimization and application domains. By separating the model expression structure from the goal and constraint conceptualizations predeﬁned modeling constructs can be reused, where we do not only separate the model structure from data, but can also abstract the structure from a speciﬁc data model. We present an XML and ontology-query based approach for this separation and demonstrate the resulting ﬂexible model integration procedure out of reusable goal and constraint types on a network ﬂow problem.

[Show BibTeX] @techreport{StapelSuhl2014,

author = {Florian Stapel AND Leena Suhl},

title = {Ontology-based Representation of Optimization Models},

year = {2014},

type = {Techreport UPB},

abstract = {This article presents a new approach for representing and processing abstract optimization models. Confronted with model and data integration tasks for distributed Decision Support Systems which are especially composed out of software services, we describe model constituents such as constraints both structurally and semantically. Within our approach, typed model constituents can be integrated into complete models and the instantiation of model constituents itself with data and data models can be wrapped into semantic software services. Besides others, this supports the automated generation of adaptors and the search for and composition of services. The basic idea of our approach is to represent the optimization models as instance knowledge of diﬀerent ontologies for both optimization and application domains. By separating the model expression structure from the goal and constraint conceptualizations predeﬁned modeling constructs can be reused, where we do not only separate the model structure from data, but can also abstract the structure from a speciﬁc data model. We present an XML and ontology-query based approach for this separation and demonstrate the resulting ﬂexible model integration procedure out of reusable goal and constraint types on a network ﬂow problem.}

}

author = {Florian Stapel AND Leena Suhl},

title = {Ontology-based Representation of Optimization Models},

year = {2014},

type = {Techreport UPB},

abstract = {This article presents a new approach for representing and processing abstract optimization models. Confronted with model and data integration tasks for distributed Decision Support Systems which are especially composed out of software services, we describe model constituents such as constraints both structurally and semantically. Within our approach, typed model constituents can be integrated into complete models and the instantiation of model constituents itself with data and data models can be wrapped into semantic software services. Besides others, this supports the automated generation of adaptors and the search for and composition of services. The basic idea of our approach is to represent the optimization models as instance knowledge of diﬀerent ontologies for both optimization and application domains. By separating the model expression structure from the goal and constraint conceptualizations predeﬁned modeling constructs can be reused, where we do not only separate the model structure from data, but can also abstract the structure from a speciﬁc data model. We present an XML and ontology-query based approach for this separation and demonstrate the resulting ﬂexible model integration procedure out of reusable goal and constraint types on a network ﬂow problem.}

}

Florian Stapel, Leena Suhl:

Techreport UPB.

[Show Abstract]

**A MINLP Approach for Planning the Renewal of Pipes in Drinking Water Networks**Techreport UPB.

**(2014)**[Show Abstract]

This article presents a novel Mixed Integer Nonlinear Programming (MINLP) approach for ﬁnding a renewal plan of pipes in a water distribution system. We formulate a MINLP model for ﬁnding the times of renewal and suited measurements of pipe dimensions in a multi-year planning horizon. The model includes a multi-period hydraulic simulation of the distribution systems behaviour thereby respecting the friction caused headloss as a nonlinear constraint. We apply the MINLP solver Bonmin to a test network and present ﬁrst numerical results. The models embedding into a general solution framework for water network problems consisting of network reduction and simulation steps in an interated way, is beign discussed. This latter discussion corresponds well to the recent results by C. Hallmann for the problem of tank planning within the mentioned solution framework that has been presented there for the ﬁrst time.

[Show BibTeX] @techreport{StapelSuhl2015,

author = {Florian Stapel AND Leena Suhl},

title = {A MINLP Approach for Planning the Renewal of Pipes in Drinking Water Networks},

year = {2014},

type = {Techreport UPB},

abstract = {This article presents a novel Mixed Integer Nonlinear Programming (MINLP) approach for ﬁnding a renewal plan of pipes in a water distribution system. We formulate a MINLP model for ﬁnding the times of renewal and suited measurements of pipe dimensions in a multi-year planning horizon. The model includes a multi-period hydraulic simulation of the distribution systems behaviour thereby respecting the friction caused headloss as a nonlinear constraint. We apply the MINLP solver Bonmin to a test network and present ﬁrst numerical results. The models embedding into a general solution framework for water network problems consisting of network reduction and simulation steps in an interated way, is beign discussed. This latter discussion corresponds well to the recent results by C. Hallmann for the problem of tank planning within the mentioned solution framework that has been presented there for the ﬁrst time.}

}

author = {Florian Stapel AND Leena Suhl},

title = {A MINLP Approach for Planning the Renewal of Pipes in Drinking Water Networks},

year = {2014},

type = {Techreport UPB},

abstract = {This article presents a novel Mixed Integer Nonlinear Programming (MINLP) approach for ﬁnding a renewal plan of pipes in a water distribution system. We formulate a MINLP model for ﬁnding the times of renewal and suited measurements of pipe dimensions in a multi-year planning horizon. The model includes a multi-period hydraulic simulation of the distribution systems behaviour thereby respecting the friction caused headloss as a nonlinear constraint. We apply the MINLP solver Bonmin to a test network and present ﬁrst numerical results. The models embedding into a general solution framework for water network problems consisting of network reduction and simulation steps in an interated way, is beign discussed. This latter discussion corresponds well to the recent results by C. Hallmann for the problem of tank planning within the mentioned solution framework that has been presented there for the ﬁrst time.}

}

**2013** (1)

Corinna Hallmann:

Techreport UPB.

[Show Abstract]

**An Approach for a Decision Support Systems to optimize Water Tanks in Water Supply Systems by combining Network Reduction, Optimization and Simulation**Techreport UPB.

**(2013)**[Show Abstract]

Since the last two decades, the water consumption in Germany is decreasing, which causes the water tanks and pipes in a water supply system to work inefficiently. This paper proposes an approach for a decision support system, which helps to decide how to plan new water tanks and resize existing tanks in water supply systems. The approach uses a combination of network reduction, mathematical optimization and hydraulic simulation. The mathematical optimization model is a nonconvex Mixed Integer Quadratically Constrained Program (MIQCP), which is solved by a piecewise linearization. As this may lead to many binary variables and therefore high computational times, the size of the water supply system model is reduced before building the optimization model. By applying several network reduction techniques there may occur some hydraulic differences between the original network model and the reduced network model. To make sure that the solution obtained in the optimization process is feasible in the original water supply system, the solution is verified by a hydraulic simulation tool.

[Show BibTeX] @techreport{Dohle2013,

author = {Corinna Hallmann},

title = {An Approach for a Decision Support Systems to optimize Water Tanks in Water Supply Systems by combining Network Reduction, Optimization and Simulation},

year = {2013},

type = {Techreport UPB},

abstract = {Since the last two decades, the water consumption in Germany is decreasing, which causes the water tanks and pipes in a water supply system to work inefficiently. This paper proposes an approach for a decision support system, which helps to decide how to plan new water tanks and resize existing tanks in water supply systems. The approach uses a combination of network reduction, mathematical optimization and hydraulic simulation. The mathematical optimization model is a nonconvex Mixed Integer Quadratically Constrained Program (MIQCP), which is solved by a piecewise linearization. As this may lead to many binary variables and therefore high computational times, the size of the water supply system model is reduced before building the optimization model. By applying several network reduction techniques there may occur some hydraulic differences between the original network model and the reduced network model. To make sure that the solution obtained in the optimization process is feasible in the original water supply system, the solution is verified by a hydraulic simulation tool.}

}

author = {Corinna Hallmann},

title = {An Approach for a Decision Support Systems to optimize Water Tanks in Water Supply Systems by combining Network Reduction, Optimization and Simulation},

year = {2013},

type = {Techreport UPB},

abstract = {Since the last two decades, the water consumption in Germany is decreasing, which causes the water tanks and pipes in a water supply system to work inefficiently. This paper proposes an approach for a decision support system, which helps to decide how to plan new water tanks and resize existing tanks in water supply systems. The approach uses a combination of network reduction, mathematical optimization and hydraulic simulation. The mathematical optimization model is a nonconvex Mixed Integer Quadratically Constrained Program (MIQCP), which is solved by a piecewise linearization. As this may lead to many binary variables and therefore high computational times, the size of the water supply system model is reduced before building the optimization model. By applying several network reduction techniques there may occur some hydraulic differences between the original network model and the reduced network model. To make sure that the solution obtained in the optimization process is feasible in the original water supply system, the solution is verified by a hydraulic simulation tool.}

}

**2012** (1)

Corinna Dohle (married name: Hallmann), Leena Suhl:

In Proceedings of the International Conference on Applied Mathematical Optimization and Modelling (APMOD). Books on Demand, pp. 404-408

[Show Abstract]

**An Optimization Model for the optimal Usage of Water Tanks in Water Supply Systems**In Proceedings of the International Conference on Applied Mathematical Optimization and Modelling (APMOD). Books on Demand, pp. 404-408

**(2012)**[Show Abstract]

In Germany, the optimization of water supply systems has gained more and more attention due to a growing cost pressure for German municipal utilities. In this work, a model is presented which optimizes the usage of water tanks. On the one hand locations of new tanks are identified, and on the other hand the size of existing tanks is optimized, subject to satisfying the demand of clients and providing the necessary amount of fire water during all time periods. The main difficulty is the consideration of the head loss equation which is required to model the hydraulic properties of a water supply system. As this equation is non-convex and quadratic the optimization model becomes a non-convex Mixed Integer Quadratically Constrained Program (MIQCP). To solve this MIQCP different solution methods are applied.

[Show BibTeX] @inproceedings{DohleSuhl2012,

author = {Corinna Dohle (married name: Hallmann) AND Leena Suhl},

title = {An Optimization Model for the optimal Usage of Water Tanks in Water Supply Systems},

booktitle = {Proceedings of the International Conference on Applied Mathematical Optimization and Modelling (APMOD)},

year = {2012},

pages = {404-408},

publisher = {Books on Demand},

abstract = {In Germany, the optimization of water supply systems has gained more and more attention due to a growing cost pressure for German municipal utilities. In this work, a model is presented which optimizes the usage of water tanks. On the one hand locations of new tanks are identified, and on the other hand the size of existing tanks is optimized, subject to satisfying the demand of clients and providing the necessary amount of fire water during all time periods. The main difficulty is the consideration of the head loss equation which is required to model the hydraulic properties of a water supply system. As this equation is non-convex and quadratic the optimization model becomes a non-convex Mixed Integer Quadratically Constrained Program (MIQCP). To solve this MIQCP different solution methods are applied.}

}

author = {Corinna Dohle (married name: Hallmann) AND Leena Suhl},

title = {An Optimization Model for the optimal Usage of Water Tanks in Water Supply Systems},

booktitle = {Proceedings of the International Conference on Applied Mathematical Optimization and Modelling (APMOD)},

year = {2012},

pages = {404-408},

publisher = {Books on Demand},

abstract = {In Germany, the optimization of water supply systems has gained more and more attention due to a growing cost pressure for German municipal utilities. In this work, a model is presented which optimizes the usage of water tanks. On the one hand locations of new tanks are identified, and on the other hand the size of existing tanks is optimized, subject to satisfying the demand of clients and providing the necessary amount of fire water during all time periods. The main difficulty is the consideration of the head loss equation which is required to model the hydraulic properties of a water supply system. As this equation is non-convex and quadratic the optimization model becomes a non-convex Mixed Integer Quadratically Constrained Program (MIQCP). To solve this MIQCP different solution methods are applied.}

}