Browsing by Author "Harjunkoski, Iiro"
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- Effective decomposition algorithm for multistage batch plant schedulingPublication . Castro, Pedro; Harjunkoski, Iiro; Grossmann, Ignacio E.This paper presents a new algorithm for the scheduling of batch plants with a large number of orders and sequence-dependent changeovers. Such problems are either intractable or yield poor solutions with full-space approaches. We use decomposition on the entire set of orders and derive the complete schedule in several iterations. The key idea is to allow for partial rescheduling without altering the main decisions in terms of unit assignments and sequencing, so that the complexity is kept at a manageable level. It has been implemented with a unit-specific continuous-time model and tested for different decomposition settings. The results show that a real-life 50-order, 17-unit, 6-stage problem can effectively be solved in roughly 6 minutes of computational time.
- Resource-task network formulations for industrial demand side management of a steel plantPublication . Castro, Pedro; Sun, Lige; Harjunkoski, IiroIn today’s energy markets, there is a growing effort toward the alignment of the industrial sector and the power grid for the sake of efficient energy distribution and consumption. In this paper, the resource-task network is used to provide a generic modeling framework for production scheduling under energy constraints. Three alternative process models for the energy-intensive melt shop of a steel plant are proposed and linked to a discrete-time formulation. The results show a trade-off between accurate representation of problem data and computational performance. By keeping track of the total energy and power consumption through time, we study the impact of fluctuating energy prices on the scheduling of operations and the economic benefits that can be obtained from the plant’s participation in the price- and incentive-based industrial demand side management programs.
- Rolling-horizon algorithm for scheduling under time-dependent utility pricing and availabilityPublication . Castro, Pedro; Harjunkoski, Iiro; Grossmann, Ignacio E.This work addresses the scheduling of continuous single-stage multiproduct plants with energy intensive processing tasks and time-dependent electricity cost and power supply. A new rolling horizon algorithm is proposed that consists of a planning model to predict the production levels and a continuous-time model for detailed scheduling. The results from a set of test problems from the literature show that the algorithm can generate global optimal solutions much more rapidly than standalone discrete or continuous-time formulations in problems involving unlimited power availability.
- Scope for industrial applications of production scheduling models and solution methodsPublication . Harjunkoski, Iiro; Maravelias, Christos T.; Bongers, Peter; Castro, Pedro; Engell, Sebastian; Grossmann, Ignacio E.; Hooker, John; Mendez, Carlos A.; Sand, Guido; Wassick, JohnThis paper gives a review on existing scheduling methodologies developed for process industries. Above all, the aim of the paper is to focus on the industrial aspects of scheduling and discuss the main characteristics, including strengths and weaknesses of the presented approaches. It is claimed that optimization tools of today can effectively support the plant level production. However there is still clear potential for improvements, especially in transferring academic results into industry. For instance, usability, interfacing and integration are some aspects discussed in the paper. After the introduction and problem classification, the paper discusses some lessons learned from industry, provides an overview of models and methods and concludes with general guidelines and examples on the modeling and solution of industrial problems.