This paper extends the study of Mathirajan et al. (Minimizing total weighted tardiness on a batch-processing machine with non-agreeable release times and due dates. Int. J. Adv. Manuf. Technol., 2010, doi: 10.1007/s00170-009-2342-y) to parallel batch-processing machine problems because these have not been examined to date. For the problem concerning compatible product families, job release times, non-identical job sizes, and varying machine capacities, we propose a mixed integer programming (MIP) model, and a number of simple dispatch-based heuristic and simulated annealing (SA) algorithms. Computational results revealed that the proposed SA is capable of obtaining similar solutions acquired by MIP within a short time. The SA algorithms outperform other heuristic algorithms with respect to solution quality.

Hybrid flow shop scheduling problems with multiprocessor tasks to minimize the makespan have been addressed and solved efficiently. Several approaches were used, including greedy methods and metaheuristics. In this paper, we proposed a mixed integer programming (MIP) model that can define explicitly and precisely the nature of a given problem. We also addressed a modified lower bound to obtain tighter bounds. Additionally, we propose different decoding methods and emphasize their importance in hybrid flow shop scheduling problems with multiprocessor tasks. By using existing test problems with n=5 in examining the proposed methods, many optimal solutions can be obtained as benchmarks for reference by the MIP model. Accordingly, the results are indicative of the influence of the decoding methods on the solutions to the hybrid flow shop problems with multiprocessor tasks.

This paper considers parallel batch-processing machine problems with compatible job family, dynamic job arrivals, and non-identical job sizes to minimize total weighted tardiness. Given that the problem of interest is non-deterministic polynomial-time (NP) hard , we propose a hybrid genetic algorithm (HGA) that incorporates batching decision and batch scheduling. Moreover, HGA is compared with simulated annealing (SA) algorithms to assess the performance of the proposed algorithm. Computational results revealed that the proposed HGA outperformed in terms of the number of best solution found, and HGA is slightly better when comparing the average TWT value.

This paper considers the scheduling problem of the four-stage open shop with parallel machines per stage observed in the chip sorting operation of light emitting diode (LED) testing. In this operation, each job (epiwafer) should be processed by the four working stages without predetermined processing route in order to separate specific LED grades. The considered problem is one of hard combinatorial optimization problems which have not been received much attention in the literature. Due to its computational complexity, in this study, two simulated annealing (SA) algorithms with different initial solutions are proposed to minimize total weighted completion times of jobs. A set of twenty benchmark solutions from a five-job problem is used to evaluate the performances of two SAs. Computational results reveal that the algorithms perform efficient and effective whatever the dimensions of problems are small or large.

In this research, the laccase mediator system (LMS) was used to modify the unbleached triploid populus tomentosa alkaline hydrogen peroxide pulp (APMP). The changes of pulp brightness were measured and the effects of LMS on the subsequent hydrogen peroxide bleaching were also determined. Besides, the fiber morphology was analyzed by ESEM, and then the obvious changes of pulp have been recovered. In a word, the LMS has obvious effect on cellulose.