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Modeling and solving the steelmaking and casting scheduling problem
Author(s) -
Armellini Davide,
Borzone Paolo,
Ceschia Sara,
Di Gaspero Luca,
Schaerf Andrea
Publication year - 2020
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12595
Subject(s) - computer science , solver , mathematical optimization , job shop scheduling , scheduling (production processes) , greedy algorithm , steelmaking , backtracking , operations research , schedule , algorithm , mathematics , materials science , metallurgy , operating system
We propose a general model for the problem of planning and scheduling steelmaking and casting activities obtained by combining common features and constraints of the operations from a real plant and the literature. For tackling the problem, we develop a simulated annealing approach based on a solution space made of job permutations, which uses as submodule a chronological constructive procedure that assigns processing times and resources to jobs. Our technique, properly tuned in a statistically principled way, is able to find good solutions for a large range of different settings and horizons. In addition, it outperforms both a greedy procedure and a constraint‐based solver developed for comparison purposes on almost all instances. Finally, we have collected several real‐world instances that we make available on the web along with the solution validator and our best results.