Supply chain-oriented permutation flowshop scheduling considering flexible assembly and setup times
Kuo‐Ching Ying, Pourya Pourhejazy, Chen-Yang Cheng, Ren-Siou Syu
Abstract
Given the significant proportion of the outsourced parts, components, and the complex assembly structure of the automobiles, agriculture machinery and heavy industry equipment, distributed production and flexible assembly are much-needed production scheduling settings to optimise their global supply chains. This research extends the distributed assembly permutation flowshop scheduling problem to account for flexible assembly and sequence-independent setup times (DPFSP_FAST) in a supply chain-like setting. For this purpose, an original mixed-integer linear programming (MILP) formulation to the DPFSP_FAST problem is first investigated. Considering makespan as the optimisation criterion, constructive heuristic and customised metaheuristic algorithms are then proposed to solve this emerging scheduling extension. Through extensive computational experiments, it is shown that the proposed algorithms outperform the existing best-performing algorithms to solve the DPFSP_FAST problem, yielding the best-found solutions in nearly all of the benchmark instances. Narrowing the gap between theory and practice, this study helps integrate the production planning scheduling across the supply chain.