Heuristic algorithms for production and transportation planning through synchronization of a serial supply chain

This study suggests an approach that synchronizes timing points found between a supplier and a buyer in a serial supply chain with one in two timing points to allow for more efficient and agile material flow. This approach is applied to the problem of finding an optimal solution for the production quantity in each production lot and the job sequence with minimum supply chain total cost and lead time. Five heuristic algorithms were developed based on simulated annealing (SA) and a genetic algorithm (GA). Of the developed heuristic algorithms, GA2 exhibited the most robustness.