Covering problem tries to locate the least number of facilities and each demand has at least one facility located within a specific distance.This paper considers a cross entropy algorithm for solving the mixed integer nonlinear programming (MINLP) for covering location model.The model is solved to determine the best covering value.Also, this paper proposes aCross Entropy (CE) algorithm consider...

This report is a summary of the theory underlying the Cross-Entropy (CE) method, as discussed in the tutorial by de Boer, Kroese, Mannor and Rubinstein [1]. For a more thorough discussion of the method and its applications, please refer to the original tutorial and the references cited in the tutorial. The CE method, pioneered by Rubinstein in 1997 as an adaptive algorithm for estimating probab...

This paper presents cross entropy (CE) based methodology for optimal design of water distribution network (WDN). Design of WDN involves selection of suitable diameter for each pipe in the network from the list of commercially available diameters. The CE methodology is applied to two bench mark WDN design problems taken from literature for validation. The first WDN problem deals with determining...

Cross-entropy optimization (CE) has proven to be a powerful tool for search in control environments. In the basic scheme, a distribution over proposed solutions is repeatedly adapted by evaluating a sample of solutions and refocusing the distribution on a percentage of those with the highest scores. We show that, in the kind of noisy evaluation environments that are common in decisionmaking dom...

No-wait job-shop scheduling (NWJSS) problem is one of the classical scheduling problems that exist on many kinds of industry with no-wait constraint, such as metal working, plastic, chemical, and food industries. Several methods have been proposed to solve this problem, both exact (i.e. integer programming) and metaheuristic methods. Cross entropy (CE), as a new metaheuristic, can be an alterna...

Parameter tuning is an important step in automatic fuzzy model identification from sample data. It aims at the determination of quasi-optimal parameter values for fuzzy inference systems using an adequate search technique. In this paper, we introduce a new hybrid search algorithm that uses a variant of the cross-entropy (CE) method for global search purposes and a hill climbing type approach to...

Virtual path management in dynamic networks poses a number of challenges related to combinatorial optimisation, fault and traffic handling. Ideally such management should react immediately on changes in the operational conditions, and be autonomous, inherently robust and distributed to ensure operational simplicity and network resilience. Swarm intelligence based self management is a candidate ...

This paper deals with estimation of probabilities of rare events in static simulation models using a fast adaptive two-stage procedure based on importance sampling and Kullback-Liebler’s cross-entropy (CE). More specifically, at the first stage we estimate the optimal parameter vector in the importance sampling distribution using CE, and at the second stage we estimate the desired rare event pr...

This paper addresses the problem of loading a finite capacity, stochastic (random) and dynamic multi-project system. The system is controlled by keeping a constant number of projects concurrently in the system. A new approach, based on the Cross-Entropy (CE) method, is proposed to determine optimal loading of the system. Through numerical experiments, we demonstrate the CE method performance an...

This study critically analyses the information-theoretic, axiomatic and combinatorial philosophical bases of the entropy and cross-entropy concepts. The combinatorial basis is shown to be the most fundamental (most primitive) of these three bases, since it gives (i) a derivation for the Kullback-Leibler cross-entropy and Shannon entropy functions, as simplified forms of the multinomial distribu...