Production Optimization and Scheduling across a Steel Plant

Harjunkoski, Iiro; Saliba, Sleman; Biondi, Matteo

doi:10.1016/b978-0-444-53711-9.50184-x

Cited by 1 publication

(1 citation statement)

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“…The algorithm involves three MILP models and one LP model solved in a sequential solution strategy. Later, addressing also a scheduling problem of a steel plant, Harjunkoski et al 45 discussed the implementation issues and benefits of planning and scheduling optimization. The authors state that reusability, flexibility, and configurability are relevant aspects that must be considered when encapsulating mathematical models in software applications to be used in industrial environments.…”

Section: Introductionmentioning

confidence: 99%

Solution Methodology for Scheduling Problems in Batch Plants

Moniz

Barbosa‐Póvoa

Sousa

et al. 2014

Ind. Eng. Chem. Res.

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This paper proposes a solution methodology for the production scheduling of batch plants. The methodology is defined by an integrated approach that simultaneously considers the representation of the scheduling problem, the optimization model, and the decision-making process. A problem representation and a mixed integer linear programing (MILP) model are developed and applied to solve a real world scheduling problem from the chemical−pharmaceutical industry. The main advantage of this approach is that it includes a general process representation that can be used across several departments of the company. Moreover, we also discuss development and implementation challenges of optimization methods for the process industry, and we provide some guidelines to mitigate existing problematic issues in this domain.

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Section: Introductionmentioning

confidence: 99%