Peer-Reviewed Journal Details
Mandatory Fields
Balough, Andrea; Garraffa, Michele; O’Sullivan, Barry; Salassa, Fabio
2022
October
Computers & Operations Research
MILP-based local search procedures for minimizing total tardiness in the No-idle Permutation Flowshop Problem
Published
()
Optional Fields
Scheduling Flowshop No-idle MILP Hybrid heuristics
146
105862
We consider the No-idle Permutation Flowshop Scheduling Problem (NPFSP) with a total tardiness criterion. We present two Mixed Integer Linear Programming (MILP) formulations based on positional and precedence variables, respectively. We study six local search procedures that explore two different neighborhoods by exploiting the MILP formulations. Our computational experiments show that two of the proposed procedures strongly outperform the state-of-the-art metaheuristic. We update 63% of the best known solutions of the instances in Taillards’ benchmark, and 77% if we exclude those instances for which we proved that the previous best known solutions are optimal.
0305-0548
https://www.sciencedirect.com/science/article/pii/S0305054822001368
10.1016/j.cor.2022.105862
Grant Details