#RUN IMPERIALISM 2 ON WINDOWS 10 KEYGEN#
The imperialist competitive algorithm has been considered by Naderi and Yazdani to cope with the HFSP with sublots and setup times. The discrete firefly algorithm has been proposed by Marichelvam to solve the bi-objective HFSP. The tabu search algorithm has been considered for the two-stage hybrid flowshop problem by Figielska. Then, the simulated annealing algorithm (SA) has been adopted by Elmi and Topaloglu to solve the problem of multi-robot scheduling.
For example, the genetic algorithm (GA) has been applied by Behnamian et al. However, with an increase in the scale of the problem, the resolution of accurate algorithms has become limited, and consequently, metaheuristic or heuristic algorithms have been used more widely to solve this problem. To solve HFSP, several researchers have applied the exact algorithms, such as the Lagrangian relaxation algorithm and the branch and bound algorithm. With regard to the conventional HFSP, many variants and solutions have been discussed by Rubén Ruiz et al. In this paper, the resource-constrained hybrid flowshop problem with energy consumption was studied, and this problem has significant practice relevance. As the major source of global warming, manufacturing activities are required to satisfy the regulations on environment protection and energy consumption. Therefore, it is necessary to investigate the RCHFS taking this into consideration. In a typical manufacturing industry, various dynamic events may occur in the actual production process, such as limited resources and machine breakdown. Compared with other types of scheduling problems, the multi-process and multi-stage characteristics of HFSP are deemed more realistic. Hybrid flowshop scheduling problem (HFSP) is a generalization of the conventional flowshop scheduling problem. The results confirmed that the proposed algorithm can solve the RCHFS with high efficiency. Furthermore, we tested the proposed algorithm based on a randomly generated set of real shop scheduling system instances and compared with the existing heuristic algorithms. Finally, we combined DICA and the simulated annealing algorithm (SA) to improve the performance of the proposed approach. Then, a decoding method considering the resource allocation was designed. In the proposed algorithm, first, each solution was represented by a two-dimensional vector, where one vector represented the scheduling sequence and another one showed the machine assignment. To address this issue, a discrete imperialist competitive algorithm (DICA) was proposed to minimize the makespan and energy consumption. However, the practical case that considers both resource-constrained and energy consumption still has rare research. The resource-constrained hybrid flowshop problem (RCHFS) has been investigated thoroughly in recent years.