Multi-objective optimization is the simultaneous consideration of two or more objective functions that are completely or partially inconflict with each other. The optimality of such optimizations is largely defined through the Pareto optimality. Multiple objective integer linear programs (MOILP) are special cases of multiple criteria decision making problems. Numerous algorithms have been desig...

The optimal allocation of integrated energy system capacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption renewable energy, which has attracted many attentions. However, optimization results are usually influenced by choice hyperparameters. To solve above problem, particle swarm algorithm is introduced to find hyperparameters algorithms. Firstly, an...

This paper proposes a multi-objective model for the economic-statistical design of the variable sample size and sampling interval multivariate exponentially weighted moving average control chart by using double warning lines. The Markov chain approach is used to obtain the statistical properties. We extend the Lorenzen and Vance cost function considering multiple assignable causes and multivari...

in this paper, a stochastic cell formation problem is studied using queuing theory framework and considering reliability. since cell formation problem is np-hard, two algorithms based on genetic and modified particle swarm optimization (mpso) algorithms are developed to solve the problem. for generating initial solutions in these algorithms, a new heuristic method is developed, which always cre...

The scheduling of multi-user remote laboratories is modeled as a multimodal function for the proposed optimization algorithm. hybrid algorithm, hybridization Nelder-Mead Simplex and Non-dominated Sorting Genetic Algorithm (NSGA), named (SNSGA), to optimize timetable problem coordinate shared access. algorithm utilizes in terms exploration NSGA sorting local optimum points with consideration pot...

Background: The recent progress and achievements in the advanced, accurate, and rigorously evaluated algorithms has revolutionized different aspects of the predictive microbiology including bacterial growth.Objectives: In this study, attempts were made to develop a more accurate hybrid algorithm for predicting the bacterial growth curve which can also be ...