Damla ArtanPelin TezcanAysu KarlıEgemen SertpoyrazDeniz MermerciEge EfekanEge DuranMustafa Arslan OrnekTezcan, PelinOrnek, M. ArslanKarlı, AysuSertpoyraz, EgemenEfekan, EgeMermerci, DenizArtan, DamlaN.M. Durakbasa , M.G. Gençyılmaz2025-10-0620239789819650583, 9783031991585, 9783031948886, 9789819667314, 9789811937156, 9783030703318, 9789811622779, 9789811969447, 9789819701056, 9789819748051978303124456821954364, 219543562195-435610.1007/978-3-031-24457-5_612-s2.0-85151134592https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151134592&doi=10.1007%2F978-3-031-24457-5_61&partnerID=40&md5=b5efb6739e98aefb95eb2636e8422a30https://gcris.yasar.edu.tr/handle/123456789/8569https://doi.org/10.1007/978-3-031-24457-5_61This study solves a one-dimensional cutting stock problem with multiple stock lengths. It is applied in a manufacturing setting where rolls of steel rods of different lengths are cut according to customer requirements. The one-dimensional cutting stock problem (CSP) is an NP-hard problem including discrete demands and capacitated planning objectives. It is solved using column generation techniques. This study aims to develop a production plan that minimizes the waste of cutting steel rods of different lengths and diameters in required lengths. The approach to solving the problem has two steps. The first step is a heuristic algorithm that produces a cutting pattern at every iteration which is then fed into a novel mathematical model to determine an optimal solution. An initial solution is obtained using randomly generated cutting patterns for the mathematical model. The algorithm terminates after a given number of iterations. The paper also proposes a Decision Support System addresses application issues and concludes with further studies. © 2023 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessColumn Generation, Cutting Stock Problem, Heuristic, Mip, Artificial Intelligence, Constraint Programming, Decision Support Systems, Integer Programming, Iron And Steel Industry, Iterative Methods, Job Shop Scheduling, Linear Programming, Production Control, Steelmaking, Column Generation, Customer Requirements, Cutting Patterns, Cutting-stock Problems, Discrete Demand, Heuristic, Mip, One-dimensional Cutting Stock Problem, Planning Objectives, Steel Rod, Heuristic AlgorithmsArtificial intelligence, Constraint programming, Decision support systems, Integer programming, Iron and steel industry, Iterative methods, Job shop scheduling, Linear programming, Production control, Steelmaking, Column generation, Customer requirements, Cutting patterns, Cutting-stock problems, Discrete demand, Heuristic, MIP, One-dimensional cutting stock problem, Planning objectives, Steel rod, Heuristic algorithmsColumn GenerationHeuristicCutting Stock ProblemMIPConference Object