Open AccessTwo-Stage Assembly Scheduling with Batch Setup Times, Time-Dependent Deterioration, and Preventive Maintenance Activities Using Meta-Heuristic Algorithms
Author(s) -
Sunwoong Jung,
Young-Bin Woo,
Shiegheun Koh,
Byung Soo Kim
Publication year - 2018
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2018/6982631
Subject(s) - harmony search , mathematical optimization , preventive maintenance , computer science , algorithm , job shop scheduling , scheduling (production processes) , chromosome , genetic algorithm , mathematics , engineering , reliability engineering , schedule , biochemistry , chemistry , gene , operating system
This article considers a two-stage assembly scheduling problem (TSASP) with batch setup times, time-dependent deterioration, and preventive maintenance activities (PMAs). The objective of this problem is to simultaneously determine the optimal component-manufacturing sequence (CMS), product-assembly sequence (PAS), number of setups, and number and position of PMAs (PPMA). First, to determine the optimal solution, a novel mixed integer linear programming model (MILP) for the proposed problem is derived. Then, a standard genetic algorithm (SGA), hybrid genetic algorithm (HGA), standard harmony search (SHS), hybrid harmony search (HHS), and harmony-search-based evolutionary algorithm (HSEA) were proposed owing to the intractability of the optimal solution for large-scale problems. SGA and SHS provide a chromosome to represent a complete solution including three decisions (CMS, PAS, and PPMA). HGA, HHS, and HSEA provide a chromosome to represent a partial solution including PAS. CMS and PPMA are found by an effective local search heuristic based on the partial solution. A computational experiment is then conducted to evaluate the impacts of the factors on the performance of the proposed algorithms.