Total tardiness minimization in permutation flowshop with deterioration consideration

In this paper, we consider a permutation flowshop scheduling problem with deteriorating jobs. The objective is to minimize the total tardiness of all jobs. A branch-and-bound algorithm incorporating with a dominance property and a lower bound is developed. Furthermore, two metaheuristic algorithms, the simulated annealing algorithm, and the particle swarm optimization method, are proposed. Finally, computational studies are given.     

A new AATP model with considering supply chain lead-times and resources and scheduling of the orders in flowshop production systems: A graph-theoretic view

The present study attempts to synchronize the scheduling problem with determining the advanced available-to-promise (AATP) in a flowshop system to enhance supplier profitability and service level. In the proposed model the AATP, scheduling and graph theory concept have been combined to find the optimum resource allocation and enable accurate estimations of machines scheduling, production costs and delivery dates. To find the near optimum solutions for the large size problems a genetic algorithm is developed, first the orders are ranked based on their scores which are estimated then the optimum cost is calculated by balancing profitability and constraints such as the availability of the machines or the available material in each workstation. Some computer simulated experiments are provided to evaluate the performance of the proposed algorithm.