A tabu memory based iterated greedy algorithm for the distributed heterogeneous permutation flowshop scheduling problem with the total tardiness criterion

Abstract

Distributed scheduling problems have been extensively studied due to their critical roles in industrial applications. Most research focuses on identical distributed factories and the objective of minimizing the makespan, ignoring the widely existing heterogeneous factories and delivery targets in reality. This paper aims to establish a distributed heterogeneous flowshop scheduling scenario with the objective of minimizing total tardiness (DHPFSP-t), and solve it using an improved iterative greedy algorithm. A mixed-integer programming model and several problem-specific properties are proposed for this novel scheduling scenario. Based on the distributed heterogeneous characteristics of the problem, four constructive algorithms are established to quickly generate initial solutions. Among them, the better solution is selected as the initial solution of the iterative greedy algorithm. To enhance the performance of the iterative greedy algorithm, the concept of tabu memory is incorporated and novel destruction and local search processes are devised. Thorough experiments are conducted to verify the effectiveness of the mixed-integer programming model of the scenario, the constructive heuristics and the improved iterative greedy algorithm. The result confirms the validity of the proposed model and the good performance of the proposed method.