A Variant Iterated Greedy Algorithm Integrating Multiple Decoding Rules for Hybrid Blocking Flow Shop Scheduling Problem

This paper studies the hybrid flow shop scheduling problem with blocking constraints (BHFSP). To better understand BHFSP, we will construct its mixed integer linear programming (MILP) model and use Gurobi solver to demonstrate correctness. Since BHFSP exists parallel machines in some processing stages, different decoding strategies can obtain makespan values for a given job sequence multiple assist algorithm find optimal value. In view of this, propose strategy that combines both forward backward select minimal objective function addition, decoding-assisted variant iterated greedy (VIG) solve above MILP model. The main novelties VIG are new reconstruction mechanism based on swap-based local reinforcement strategy, which enrich diversity solutions explore neighborhoods more deeply. evaluation is conducted against six state-of-the-art algorithms from literature. 100 tests showed average relative percentage increase (RPI) 1.00% 89.6% than comparison average, respectively. Therefore, suitable studied BHFSP.