Marianthi G. Ierapetritou

Learn More
The current manufacturing environment for process industry has changed from a traditional single-site, single market to a more integrated global production mode where multiple sites are serving a global market. In this paper, the integrated planning and scheduling problem for the multisite, multiproduct batch plants is considered. The major challenge for(More)
Uncertainty is a very important concern in production scheduling since it can cause infeasibilities and production disturbances. Thus scheduling under uncertainty has received a lot of attention in the open literature in recent years from chemical engineering and operations research communities. The purpose of this paper is to review the main methodologies(More)
The problem addressed in this work is to develop a comprehensive mathematical programming model for the efficient scheduling of oil-refinery operations. Our approach is first to decompose the overall problem spatially into three domains: the crude-oil unloading and blending , the production unit operations and the product blending and delivery. In(More)
Keywords: Benders decomposition Mixed integer programming Multi-generation of cuts Maximum feasible subsystem a b s t r a c t A new multi-generation of cuts algorithm is presented in this paper to improve the efficiency of Benders decomposition approach for the cases that optimality cuts are difficult to be achieved within the iterations of the algorithm.(More)
In this article, we propose a new algorithm for the resolution of mixed integer bi-level linear problem (MIBLP). The algorithm is based on the decomposition of the initial problem into the restricted master problem (RMP) and a series of problems named slave problems (SP). The proposed approach is based on Benders decomposition method where in each iteration(More)
The solution of large-scale scheduling problems involving the production of hundreds different products using a variety of process unit operations are typical for chemical and pharmaceutical companies. These problems however are translated to mathematical models involving a computationally infeasible number of variables and constraints independent of the(More)
Motivation: A novel mixed-integer optimization framework is proposed for the design and analysis of regulatory networks. The model combines gene expression data and prior biological knowledge regarding the potential for regulatory interactions between genes and their corresponding transcription factors. The formalism provides significant advantages over(More)
This paper presents a new approach towards parametric analysis of MINLP models in the context of process synthesis problems under uncertainty. The approach is based on the idea of High Dimensional Model Representation technique which utilize a reduced number of model runs to build an uncertainty propagation model that expresses the variability of optimal(More)
The idea of cyclic scheduling is commonly utilized to address short-term scheduling problems for multiproduct batch plants under the assumption of relatively stable operations and product demands. It requires the determination of optimal cyclic schedule, thus greatly reducing the size of the overall scheduling problems with large time horizon. In this paper(More)