This paper considers a multi-period, multi-product inventory-routing problem in a two-level supply chain consisting of a distributor and a set of customers. This problem is modeled with the aim of minimizing bi-objectives, namely the total system cost (including startup, distribution and maintenance costs) and risk-based transportation. Products are delivered to customers by some heterogeneous ...

This paper addresses an unrelated multi-machine scheduling problem with sequence-dependent setup time, release date and processing set restriction to minimize the sum of weighted earliness/tardiness penalties and the sum of completion times, which is known to be NP-hard. A Mixed Integer Programming (MIP) model is proposed to formulate the considered multi-criteria problem. Also, to solve the mo...

Unlike commonly used methods, in this paper, we have introduced a new approach for designing fuzzy controllers. In this approach, we have simultaneously optimized both objective functions of a supply chain over a two-dimensional space. Then, we have obtained a spectrum of optimized points, each of which represents a set of optimal parameters which can be chosen by the manager ...

Combining classical technologies with modern intelligent algorithms, this paper introduces a new approach for the optimisation and modelling of EAF-based steel-making process based on multi-objective using evolutionary computing machine learning. Using large amount real-world historical data containing 6423 consecutive EAF heats collected from melt shop in an established steel plant work not on...

an alternative for decreasing risk for knowledge workers is effective & optimized work break.major performance criteria in r&d; based organization is successful projects. selection of opproporiate members can be a most effect on the projects achievement. but as the selection of r&d; special members lead to decrease of risk, repeatative participation of this people in the same project lead to kn...

Objective: In general, financial time series such as stock indexes have nonlinear, mutable and noisy behavior. Structural and statistical models and machine learning-based models are often unable to accurately predict series with such a behavior. Accordingly, the aim of the present study is to present a new hybrid model using the advantages of the GMDH method and Non-dominated Sorting Genetic A...