Arash Motaghedi-Larijani, Kamyar Sabri-Laghaie , Mahdi Heydari,
Volume 21, Issue 4 (12-2010)
Abstract
In this paper flexible job-shop scheduling problem (FJSP) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. As the problem belongs to the class of NP-Hard problems, a new hybrid genetic algorithm is proposed to obtain a large set of Pareto-optimal solutions in a reasonable run time. The algorithm utilizes from a local search heuristic for improving the chance of obtaining more number of global Pareto-optimal solutions. The solution method uses from a perturbed global criterion function for guiding the search direction of the hybrid algorithm. Computational experiences show that the hybrid algorithm has superior performance in contrast to previous studies .
Moreza Rasti-Bazroki, Pegah Amini,
Volume 32, Issue 3 (9-2021)
Abstract
Due to the intensity of competition and economical condition in different countries, a group of manufacturers tried to add new products in their product portfolios in order to gain superiority against their competitors. However, the strategy and the manner of adding the products to the portfolio is one of the biggest challenges in the manufacturing process. As a result, researchers have used a variety of methods to evaluate the alternatives, such as ranking, mathematical optimization and multi criteria decision making. Hybrid methods using multi criteria decision making have gained popularity in recent years. This article uses a novel hybrid strategy using multi criteria decision making in order to find the best alternative. It is concluded that the ‘making’ alternative is superior to joint venturing and buying alternatives using the net outranking flow index.
