Minimization of total tardiness on unrelated parallel machines with sequence- and machine-dependent setup times under due date constraints

2010 ◽  
Vol 53 (1-4) ◽  
pp. 353-361 ◽  
Author(s):  
Shih-Wei Lin ◽  
Chung-Cheng Lu ◽  
Kuo-Ching Ying
Keyword(s):  
Parallel Machines ◽  
Setup Times ◽  
Total Tardiness ◽  
Unrelated Parallel Machines ◽  
Due Date ◽  
Dependent Setup Times

Exact algorithms for a scheduling problem with unrelated parallel machines and sequence and machine-dependent setup times

2008 ◽  
Vol 35 (4) ◽  
pp. 1250-1264 ◽  
Author(s):  
Pedro Leite Rocha ◽  
Martín Gómez Ravetti ◽  
Geraldo Robson Mateus ◽  
Panos M. Pardalos
Keyword(s):  
Parallel Machines ◽  
Exact Algorithms ◽  
Setup Times ◽  
Scheduling Problem ◽  
Unrelated Parallel Machines ◽  
Dependent Setup Times

scholarly journals Minimizing total tardiness for the order scheduling problem with sequence-dependent setup times using hybrid matheuristics

2022 ◽  
Vol 13 (2) ◽  
pp. 223-236 ◽  
Author(s):  
Massimo Pinto Antonioli ◽  
Carlos Diego Rodrigues ◽  
Bruno de Athayde Prata
Keyword(s):  
Setup Times ◽  
Total Tardiness ◽  
Mixed Integer ◽  
Order Scheduling ◽  
Due Date ◽  
Customer Order ◽  
Large Size ◽  
Milp Model ◽  
Dependent Setup Times ◽  
Customer Order Scheduling

This paper aims at presenting a customer order scheduling environment in which the setup times are explicit and depend on the production sequence. The considered objective function is the total tardiness minimization. Since the variant under study is NP-hard, we propose a mixed-integer linear programming (MILP) model, an adaptation of the Order-Scheduling Modified Due-Date heuristic (OMDD) (referred to as Order-Scheduling Modified Due-Date Setup (OMMD-S)), an adaptation of the Framinan and Perez-Gonzalez heuristic (FP) (hereinafter referred to as Framinan and Perez-Gonzalez Setup (FP-S)), a matheuristic with Same Permutation in All Machines (SPAM), and the hybrid matheuristic SPAM-SJPO based on Job-Position Oscillation (JPO). The algorithms under comparison have been compared on an extensive benchmark of randomly generated test instances, considering two performance measures: Relative Deviation Index (RDI) and Success Rate (SR). For the small-size evaluated instances, the SPAM is the most efficient algorithm, presenting the better values of RDI and SR. For the large-size evaluated instances, the hybrid matheuristic SPAM-JPO and MILP model are the most efficient methods.

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