Optimal plate design problem in steel production

Abstract

In this paper, we address a new optimal plate design problem in steel production, in which slab selection is jointly considered. On the basis of the underlying features, the problem is formulated as a mixed integer nonlinear programming (MINLP) model with generalized disjunctive programming (GDP) constraints. A logic-based outer approximation (L-OA) algorithm is proposed to solve the problem. Specifically, a two-stage heuristic method is designed to initialize the L-OA algorithm. Numerical results are presented to demonstrate that the proposed L-OA algorithm and the heuristic method are effective and computationally efficient.

A two‐stage solution method for the design problem of medium‐thick plates in steel plants

“…Step 3 After generating the initial population, a selection function is established. The fitness function is subtracted from the largest fitness function in the current population so that the individuals with the smallest space utilisation are eliminated, as shown in Equation (15).…”

“…They proposed a decentralised search algorithm for directed local search that utilises scene aggregation to reduce variable constraints. The average running time of this algorithm was 60.09 s. Zhao et al [15] constructed a band crate model with the goal of consuming the least amount of raw material and proposed a two-stage algorithm based on a logic-based outer approximation. The algorithm achieves optimal solutions within a time range of 20-5000 s, with a maximum gap of 10% between the initial upper bound and optimal solution for all instances.…”