Adaptive large neighborhood search to solve multi-level scheduling and assignment problems in broiler farms

This research aimed to present a solution to the problem of production scheduling and assignment in broiler farms, which thus enabled the farms to achieve maximum profit. In the operation of farms, there are many factors that affect profits, such as the number of broilers being consistent with the demand of production plants, including profits from the sales and transportation costs. Therefore, we formulated a mathematical model and tested it while using three problem groups through the Lingo v.11 program. The results indicated that this mathematical model could find a suitable solution. However, finding the best solution had time constraints, which resulted in various other problems that prevented a search for an optimal solution due to time consumption exceeding 72 h. We developed an algorithm using the Adaptive Large Neighborhood Search (ALNS) method in order to find another possible solution using a shorter time period, which consisted of ALNS1, ALNS2, and ALNS3. These algorithms are based on a combination of the method of destruction solutions and methods accepting different solutions. We aimed to effectively solve the problems and ensure that they are appropriate for the case study, a broiler farm in Buriram. When comparing the algorithm efficiency with the Lingo v.11 program, it was found that the ALNS1 algorithm was the most suitable for finding the optimal solution in the shortest time, which resulted in a 5.74% increase in operating profits.