This study presents an interval-fuzzy De Novo programming (IFDNP) method for planning water-resourcesmanagement systems under uncertainty. IFDNP is derived by incorporating the concepts of interval parameters and fuzzy sets within a De Novo programming framework. IFDNP has the advantages in constructing optimal system design through introducing the flexibility into the available resources in the model's constraints. Moreover, IFDNP allows the decision makers to achieve a metaoptimal system performance and improve the performance of compromise solutions, and it is effective for dealing with the system design problems involving multiple objectives and multiple uncertainties. The IFDNP is then applied to a case study of designing an inexact optimal system with budget limit for water resources management and planning. Various scenarios that are associated with different levels of economic implication consequences and water allocation patterns under uncertainty are analyzed. Results can help decision makers to evaluate alternatives of system designs and to determine which of these designs can most efficiently achieve the desired economic objective constrained by limited resources.

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In this paper, we consider a general system whose reliability can be characterized with respect to a periodic timedependent utility function related to the system performance in time. When an anomaly occurs in the system operation, a loss of utility is incurred that depends on the instance of the anomaly's occurrence and its duration. Under exponential anomalies' inter-arrival times and general distributions of maintenance time duration, we analyze the long-term average utility loss and we show that the expected utility loss can be written in a simple form. This allows us to evaluate the expected utility loss of the system in a relatively simple way, which is quite useful for the dimensioning of the system at the design stage. To validate our results, we consider as a use case scenario a cellular network consisting of 660 base stations. Using data provided by the network operator, we validate the periodic nature of users' traffic and the exponential distribution of the anomalies inter-arrival times, thus allowing us to leverage our results and provide reliability scores to the aforementioned network.

In this paper, we consider a general system whose reliability can be characterized with respect to a periodic timedependent utility function related to the system performance in time. When an anomaly occurs in the system operation, a loss of utility is incurred that depends on the instance of the anomaly's occurrence and its duration. Under exponential anomalies' inter-arrival times and general distributions of maintenance time duration, we analyze the long-term average utility loss and we show that the expected utility loss can be written in a simple form. This allows us to evaluate the expected utility loss of the system in a relatively simple way, which is quite useful for the dimensioning of the system at the design stage. To validate our results, we consider as a use case scenario a cellular network consisting of 660 base stations. Using data provided by the network operator, we validate the periodic nature of users' traffic and the exponential distribution of the anomalies inter-arrival times, thus allowing us to leverage our results and provide reliability scores to the aforementioned network.