Experimental data for "Lot-Sizing Optimization Model for the Cold-formed Steel Profiles Production Planning"

This dataset supplements a manuscript currently under review. The reference will be updated upon publication. Dataset used in the experimentation reported in the article: Lot-Sizing Optimization Model for the Cold-formed Steel Profiles Production Planning [more details: pending] [DOI, pending] Dataset Contents 1. Problem Instances The problem instances arise from the production planning and manufacturing processes of a Chilean manufacturer of cold-formed steel profiles, covering a two-month operating period of 24 working days each month.File: All_Instances.7zThe problem instances were developed using base data from the production planning and manufacturing process of a Chilean manufacturer of cold-formed steel profiles over a six-month operating period of 24 working days per month. The details regarding the construction of these instances are presented in the article "Lot-Sizing Optimization Model for the Cold-formed Steel Profiles Production Planning" [DOI].The dataset includes 49 folders, each combining different demand levels and order quantities. For each combination of demand factors and the number of orders, 100 instances (4,900 total).Demand factors: 70%, 80%, 90%, 100%, 110%, 120%, and 130%.Number of orders: Random integers uniformly distributed with means of 35, 45, 55, 65, 75, 85, and 95 orders, with a ±5 variation. 2. Solution Reports A compressed file is provided for each of the following solution runs:Optimal runs for all instances: File "optimal runs.7z" (3,533 feasible instances)Time-limited runs for all instances (30, 60, and 120 seconds): Files "Reports 30s time limit.zip", "Reports 60s time limit.zip", and "Reports 120s time limit.zip" (1,032 instances)Time-limited runs for hard instances (41 selected instances): File "Reports Hard instances 300s time limit.zip" (41 instances) 3. Summary of Results This file contains the results for each experiment-instance, including Objective Value, Runtime, and Status. It has its own README. 4. Model Implementation The implementation of the optimization model is provided in the LotSizing.ipynb file, developed using: Programming Language: Julia Platform: JupyterLab Modeling Language: JuMP Solver: HiGHS