Seyed Taghi Akhavan Niaki

TL;DR: Bi-objective optimization of a multi-product multi-period three-echelon supply-chain-network problem is aimed and parameter-tuned NSGA-II and NRGA with a modified priority-based encoding are proposed to show the applicability.

TL;DR: Results show that the ANN that uses the most influential features is able to forecast the daily direction of S&P 500 significantly better than the traditional logit model and indicate that ANN could significantly improve the trading profit as compared with the buy-and-hold strategy.

TL;DR: In this research, an economic order quantity (EOQ) model is first developed for a two-level supply chain system consisting of several products, one supplier and one-retailer, in which shortages are backordered, the supplier's warehouse has limited capacity and there is an upper bound on the number of orders.

TL;DR: This paper presents a new methodology to solve multi-response statistical optimization problems that integrates desirability function and simulation approach with a genetic algorithm.

TL;DR: In this paper, an artificial neural network based model is proposed to diagnose faults in out-of-control conditions and to help identify aberrant variables when Shewhart-type multivariate control charts based on Hotelling's T2 are used.