Maria da Conceição Cunha

Tabu search algorithms for water network optimization

Abstract In this paper we propose a tabu search algorithm to find the least-cost design of looped water distribution networks. The mathematical nature of this optimization problem, a nonlinear mixed integer problem, is at the origin of a multitude of contributions to the literature in the last 25 years. In fact, exact optimization methods have not been found for this type of problem, and, in the past, classical optimization methods, like linear and nonlinear programming, were tried at the cost of drastic simplifications. Tabu search is a valuable heuristic technique for solving problems cast in combinatorial form. This is based on the human memory process and uses an iterative neighborhood search procedure in an attempt to avoid becoming trapped in local optima. The use of such a heuristic procedure to solve the aforementioned problem needs particular tailoring to produce high quality solutions. In this paper we present the essential features of the algorithm and the results obtained when it is applied to some of the classical water distribution network case studies appearing in the literature. The results are very promising and demonstrate the usefulness of tabu search algorithms in solving this kind of optimization problem.

On Solving Aquifer Management Problems with Simulated Annealing Algorithms

Aquifer systems play an essential role in meeting the ever increasing use of water for different purposes. Proper design and management of such systems should therefore be a very important matter of concern, not only to ensure that water will be available in adequate quantity (and quality) to satisfy demands but also to guarantee that this would be done in an optimal manner. This paper presents a model serving to define which water supply structures (especially pumping equipment and pipes) should be installed in order to minimize the sum of set-up costs and operation costs while satisfying demands, using a heuristic approach based on simulated annealing. Annealing algorithms are random local search optimization algorithms that allow, at least in theory and in probability, the determination of a global optimum of a (possibly constrained) function.Aquifer systems play an essential role in meeting the ever increasing use of water for different purposes. Proper design and management of such systems should therefore be a very important matter of concern, not only to ensure that water will be available in adequate quantity (and quality) to satisfy demands but also to guarantee that this would be done in an optimal manner. This paper presents a model serving to define which water supply structures (especially pumping equipment and pipes) should be installed in order to minimize the sum of set-up costs and operation costs while satisfying demands, using a heuristic approach based on simulated annealing. Annealing algorithms are random local search optimization algorithms that allow, at least in theory and in probability, the determination of a global optimum of a (possibly constrained) function.

OPTIMAL SPACE-TIME COVERAGE AND EXPLORATION COSTS IN GROUNDWATER MONITORING NETWORKS

A method to determine the optimal subset of stations from a reference level groundwater monitoring network is proposed. The method considers the redundancy of data from historical time series, the times associated with the total distance required to run through the entire monitoring network, and the sum of the times for each monitoring station. The method was applied to a hypothetical case-study consisting of a monitoring network with 32 stations. Cost-benefit analysis was performed to determine the number of stations to include in the new design versus loss of information. This optimisation problem was solved with simulated annealing. Results showed that the relative reduction in exploration costs more than compensates for the relative loss in data representativeness.

Multi-objective optimization of water distribution systems based on a real options approach

Abstract This paper describes a multi-objective optimization model including Real Options concepts for the design and operation of water distribution networks. This approach is explained through a case study with some possible expansion areas defined to fit different future scenarios. A multi-objective decision model with conflicting objectives is detailed. Also, environmental impacts are considered that take into account not only the life cycle carbon emissions of the different materials used during the construction of the networks but also the emissions related to energy consumption during operation. These impacts are translated by giving a cost to each tonne of carbon dioxide emitted. This work presents a new multi-objective simulated annealing algorithm linked to a hydraulic simulator to verify the hydraulic constraints, and the results are represented as points on the Pareto front. The results show that the approach can deal explicitly with conflicting objectives, with environmental impacts and with future uncertainty.

Robust Design of Water Distribution Networks for a Proactive Risk Management

In the last three decades the optimal design of water distribution systems problem has been studied by a great many researchers, and this has resulted in the development of a large number of models and the application of optimization techniques. The design of these infrastructures is based on future predefined and perfectly known working conditions for the water distribution networks, a premise that may direct the optimization process to solutions which, although optimal for the imposed scenario, may perform badly if reality turns out to be significantly different. In fact the working conditions can be disrupted by accidents such as broken pipes or reservoirs, technical failures, change in demand, etc. In the context of a proactive attitude toward risk, it is important to consider these aspects at the design phase. This paper presents a robust optimization-based approach for designing a water distribution network aimed at obtaining solutions that can cope with the uncertainty of the network’s working cond...

Optimization of the Operation of Large-Scale Multisource Water-Supply Systems

This paper describes a simulation-optimization model aimed at helping water utilities determine the best way to operate large-scale multisource water-supply systems. The operation of water systems is optimized taking into account the principal planning objectives defined for interventions that include reducing operating costs, satisfying demand, delivering water of appropriate quality, and not prompting the use of emergency sources. The model allows that these planning objectives may not be completely fulfilled in critical circumstances (e.g., droughts) when goals have to be prioritized by the water utilities. The model is a highly nonlinear programming problem and is solved with the general algebraic modeling system (GAMS), using the MINOS algorithm (GAMS/MINOS). The application of the model to the multimunicipal urban water-supply system of the Algarve shows its capabilities for optimizing the operation considering economic and noneconomic goals included in the objective function and to cope with future...

Using Real Options in the Optimal Design of Water Distribution Networks

AbstractWater supply systems have to satisfy water needs in terms of quantity and quality. The constant changes in urban areas require the regular adaptation of the water supply infrastructure to meet new circumstances. However, decisions to design and operate water networks have to be taken under uncertainty. Flexibility is thus the key to more robust and confident decisions. An approach called real options (ROs) can be used in these situations. This approach makes it possible to use adaptive strategies in the decision process. Some decisions can be delayed pending future conditions. Water distribution systems are very costly and complex infrastructures. Once built, their operating structure cannot be changed significantly. This work presents an innovative ROs approach to define an objective function to cope with some future scenarios in a specific case study. The objective of our proposed model is to find a minimum cost solution for the first period of a planning horizon, while considering various possi...

Optimal Extension of Rain Gauge Monitoring Network for Rainfall Intensity and Erosivity Index Interpolation

Rain gauge monitoring networks are highly important for precipitation and erosion estimation. In general, measurement accuracy depends on the precipitation as well as on the network size and design. This paper proposes a method for assessing the optimal location of new monitoring stations within an existing rain gauge network. It takes account of precipitation as well as the prediction accuracy of rainfall erosivity. A well known geostatistical variance-reduction method is applied jointly with simulated annealing as an algorithm for objective function minimization. With respect to the first objective, the kriging variance of intensity estimation is minimized considering a reference duration of one hour. The erosion-related objective, meanwhile, is focused on the minimization of the kriging variance of estimation of the logarithm of the erosivity factor. The spatial variability of rainfall observed during the extreme rainfall event recorded in March 1973, which was the heaviest rainfall event in the period...

Groundwater cleanup: The optimization perspective (a literature review)

Contamination of groundwater resources is becoming a serious environmental problem. Huge investments are usually needed to contain and to restore contaminated groundwater, thus reducing costs is challenging. Simulation-optimization techniques can obviously play an important role here. The application of these techniques to reducing remediation costs has become an area of active research, and much progress has been made towards developing mathematical models for groundwater management and remediation. These models are built with a view to aiding the proper identification of the most cost-effective measures to be taken, while satisfying a set of stated physical, technological, legal and other constraints. The literature shows that during the last fifteen years a great deal of work has been done on this subject. This paper presents a synthesis of the optimization models reported in the literature on this topic, and discusses both their mathematical characteristics and their suitability.Contamination of groundwater resources is becoming a serious environmental problem. Huge investments are usually needed to contain and to restore contaminated groundwater, thus reducing costs is challenging. Simulation-optimization techniques can obviously play an important role here. The application of these techniques to reducing remediation costs has become an area of active research, and much progress has been made towards developing mathematical models for groundwater management and remediation. These models are built with a view to aiding the proper identification of the most cost-effective measures to be taken, while satisfying a set of stated physical, technological, legal and other constraints. The literature shows that during the last fifteen years a great deal of work has been done on this subject. This paper presents a synthesis of the optimization models reported in the literature on this topic, and discusses both their mathematical characteristics and their suitability.

Optimal Management of a Groundwater System for Seasonally Varying Agricultural Production

We discuss the problem of programming the optimal operation of an aquifer system hydraulically linked to a river, using a set of predesigned hydraulic structures, in order to meet agricultural requirements. The focus is on two fundamental aspects: (1) the choice of a model that adequately reflects the physical, dynamic behavior of such a system and possesses characteristics allowing for the treatment of the problem through optimization techniques, and (2) the formulation of the problem as an optimization program. The model includes a physical component, based on the influence coefficient (impulsional response) concept and the principle of superposition, and an agricultural production function, elaborated in such a way as to reflect the dynamic process of plant development, that is, the seasonal life cycle of the crops and the effect of changing hydrological conditions on the latter. Results obtained on a test scenario illustrate the approach.