Vicente S. Fuertes-Miquel

Design of Water Distribution Networks using a Pseudo-Genetic Algorithm and Sensitivity of Genetic Operators

Genetic algorithms (GA) are optimization techniques that are widely used in the design of water distribution networks. One of the main disadvantages of GA is positional bias, which degrades the quality of the solution. In this study, a modified pseudo-genetic algorithm (PGA) is presented. In a PGA, the coding of chromosomes is performed using integer coding; in a traditional GA, binary coding is utilized. Each decision variable is represented by only one gene. This variation entails a series of special characteristics in the definition of mutation and crossover operations. Some benchmark networks have been used to test the suitability of a PGA for designing water distribution networks. More than 50,000 simulations were conducted with different sets of parameters. A statistical analysis of the obtained solutions was also performed. Through this analysis, more suitable values of mutation and crossover probabilities were discovered for each case. The results demonstrate the validity of the method. Optimum solutions are not guaranteed in any heuristic method. Hence, the concept of a “good solution” is introduced. A good solution is a design solution that does not substantially exceed the optimal solution that is obtained from the simulations. This concept may be useful when the computational cost is critical. The main conclusion derived from this study is that a proper combination of population and crossover and mutation probabilities leads to a high probability that good solutions will be obtained.

A MODEL-DRIVEN DECISION SUPPORT SYSTEM FOR REALLOCATION OF SUPPLY TO ORDERS UNDER UNCERTAINTY IN CERAMIC COMPANIES

AbstractIn ceramic companies, uncertainty in the tone and gage obtained in first quality units of the same finished good (FG) entails frequent discrepancies between planned homogeneous quant- ities and real ones. This fact can lead to a shortage situation in which certain previously committed customer orders cannot be served because there are not enough homogeneous units of a specific FG (i.e., with the same tone and gage). In this paper, a Model-Driven Decision Support System (DSS) is proposed to reassign the actual homogeneous stock and the planned homogeneous sublots to already committed orders under uncertainty by means of a mathematical programming model (SP-Model). The DSS functionalities enable ceramic decision makers to generate different solutions by changing model options. Uncertainty in the planned homogeneous quantities, and any other type of uncertainty, is managed via scenarios. The robustness of each solution is tested in planned and real situations with another DSS functionality based on a...

Subatmospheric pressure in a water draining pipeline with an air pocket

ABSTRACT An air pocket’s behaviour inside of a pipeline during transient conditions is of great importance due to its effect on the safety of the hydraulic system and the complexity of modeling its behaviour. The emptying process from water pipelines needs more assessment because the generation of troughs of subatmospheric pressure may lead to serious damage. This research studies the air pocket parameters during an emptying process from a water pipeline. A well-equipped experimental facility was used to measure the pressure and the velocity change throughout the water emptying for different air pocket sizes and valve opening times. The phenomenon was simulated using a one-dimensional (1D) developed model based on the rigid formulation with a non-variable friction factor and a constant pipe diameter. The mathematical model shows good ability in predicting the trough of subatmospheric pressure value as the most important parameter which can affect the safety of hydraulic systems.

Transient phenomena during the emptying process of a single pipe with water–air interaction

ABSTRACT Emptying pipelines can be critical in many water distribution networks because subatmospheric pressure troughs could cause considerable damage to the system due to the expansion of entrapped air. Researchers have given relatively little attention to emptying processes compared to filling processes. The intricacy of computations of this phenomenon makes it difficult to predict the behaviour during emptying, and there are only a few reliable models in the literature. In this work, a computational model for simulating the transient phenomena in single pipes is proposed, and was validated using experimental results. The proposed model is based on a rigid column to analyse water movement, the air–water interface, and air pocket equations. Two practical cases were used to validate the model: (1) a single pipe with the upstream end closed, and (2) a single pipe with an air valve installed on the upstream end. The results show how the model accurately predicts the experimental data, including the pressure oscillation patterns and subatmospheric pressure troughs.

A decision support tool for the order promising process with product homogeneity requirements in hybrid Make-To-Stock and Make-To-Order environments. Application to a ceramic tile company

Abstract Order promising in manufacturing systems that produce non-uniform units of the same finished good becomes a more complex process when customer orders need to be served with homogeneous units. To facilitate this task, we propose a mathematical model-based decision tool to support the order promising process according to product homogeneity requirements in hybrid Make-To-Stock (MTS) and Make-To-Order (MTO) contexts. In these manufacturing environments, the comparison of Available-To-Promise (ATP) and/or Capable-To-Promise (CTP) quantities with homogeneous ones ordered by customers is necessary during the order commitment. To properly deal with customers’ product uniformity requirements, different ATP consumption rules are implemented by defining a novel objective function. CTP modelling in these systems also entails having to address new aspects, such as estimating future homogeneous quantities in additional lots to the master plan, accomplishing minimum lot sizes and saving in setups when programming new lots. By including CTP in the order promising model, a closer integration with the master production schedule is achieved. The resulting mathematical model was applied to a ceramic tile company in different supply scenarios and execution modes, and at several availability levels (ATP and ATP&CTP). The results validate model performance and provide insights into the impact of ATP consumption rules on the profits made from committed customer orders in different scenarios for the specific ceramic tile company.

Configurable DSS for Uncertainty Management by Fuzzy Sets

Abstract In this paper, we propose a Configurable Model Based DSS capable of dealing with generic problems being modeled by Linear Programming (LP) and by Fuzzy Sets (FS) in a deterministic and uncertain context, respectively. The DSS assumes the transformation of the original model with fuzzy coefficients into an equivalent crisp model where the fuzzy coefficients are represented as alpha-parametric values, which can vary in a predefined interval based on the alpha parameter. Through the DSS, solutions obtained by solving the deterministic model and the equivalent crisp model for different alpha-values are compared based on the objectives and performance parameters defined by the Decision Maker (DM). Due to the uncertainty in data, expected performance of solutions can change under real situations. The DSS allows simulating future real situations by generating different projections of uncertain parameters. New performance of previously generated solutions can be tested under these hypothetical real situations by means a third model (Model for the Real Performance Assessment). Finally, the DM can choose the solution to be implemented taking into account the performance of solutions under planned and real uncertainty.