Modelling of heuristic distribution algorithm to optimize flexible production scheduling in Indian industry

Multi-objective scheduling with the NP-dependent relay preparation time becomes difficult because the complexity of the optimization increases within a reasonable time. Research methods have become a more important option to solve the difficult problems of NP because there are more powerful solutions and a great potential to require biology in a reasonable time. In the present work, Two Heuristic Algorithms are modelled and the best algorithm among those two Heuristics is selected after few comparisons 3M to 5M, this can optimize the scheduling processes up to 10x10 jobs i.e. 10 machines and 10 jobs. In context of Heuristic optimization, the results clearly show the variation in times (decrease) of all-time dependents i.e. 46% decrease, when the increase in machines and jobs are considered, therefore, it implicates the error of 0.468 as the make-span decreased by 221 minutes. The proposed model gives a large edge in minimization of make-span i.e., 40-50% decrease in the production times, and it can produce even more when the number of sources and jobs are more. Therefore, the optimized error of 0.456 than the mathematical data and hence, this model is validated

A branch-and-bound algorithm for the prize-collecting single-machine scheduling problem with deadlines and total tardiness minimization

We study a prize-collecting single-machine scheduling problem with hard deadlines, where the objective is to minimize the difference between the total tardiness and the total prize of the selected jobs. This problem is motivated by industrial applications, both as a stand-alone model and as a pricing subproblem in column-generation algorithms for parallel machine scheduling problems. A preprocessing rule is devised to identify jobs that cannot belong to any optimal schedule. The resulting reduced problem is solved to optimality by a branch-and-bound algorithm and two integer linear programming formulations. The algorithm and the formulations are experimentally compared on randomly generated benchmark instances