New Iterative Mip-Based Neighborhood Search Heuristics For Single And Parallel Machine Capacitated Lot-Sizing And Scheduling

Abstract

The primary objective of this study was to develop engineering-based, high-quality solutions to the challenging single-machine batch sizing and scheduling problem with sequence-dependent preparation time and cost. Heuristics for general use. Matching metaheuristics and mixed integer programming. Experience is required to develop competitive solutions to this NP-hard problem, as commercial solvers cannot even manage medium-sized versions of it. On the basis of the MIP formulas, construction, development, and research experiences are generated. As demonstrated by a series of mathematically calculated experiments, the fundamental method, a local search test based on random MIPs, is successful and efficient for solving medium to large problems.