An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm

Ibrahim, I. and Ibrahim, Z. and Ahmad, Hamzah and Jusof, M.F.M. and Yusof, Z.M. and Nawawi, S.W. and Mubin, M. (2015) An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm. International Journal of Advanced Manufacturing Technology, 79 (5-8). pp. 1363-1376. ISSN 0268-3768

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Abstract

Assembly sequence planning (ASP) becomes one of the major challenges in product design and manufacturing. A good assembly sequence leads to reduced costs and duration in the manufacturing process. However, assembly sequence planning is known to be a classical NP-hard combinatorial optimization problem; ASP with many product components becomes more difficult to solve. In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. As in the gravitational search algorithm, the RBMSGSA incorporates Newton's law of gravity, the law of motion, and a rule that makes each assembly component of each individual solution occur once based on precedence constraints; the best feasible sequence of assembly can then be determined. To verify the feasibility and performance of the proposed approach, a case study has been performed and a comparison has been conducted against other three approaches based on simulated annealing (SA), a genetic algorithm (GA), and binary particle swarm optimization (BPSO). The experimental results show that the proposed approach has achieved significant improvement in performance over the other methods studied.

Item Type: Article
Additional Information: ISI Document Delivery No.: CL9FX Times Cited: 0 Cited Reference Count: 32 Cited References: Blum C, 2003, ACM COMPUT SURV, V35, P268, DOI 10.1145/937503.937505 Bonneville F., 1995, IEEE S EM TECHN FACT, V2, P231 Chakrabarty S, 1997, IEEE T ROBOTIC AUTOM, V13, P14, DOI 10.1109/70.554344 Chen WC, 2008, EXPERT SYST APPL, V34, P1777, DOI 10.1016/j.eswa.2007.01.034 Cheng Hui, 2009, International Journal of Advanced Manufacturing Technology, V42, DOI 10.1007/s00170-008-1661-8 Choi Y-K, 2008, INT J ADV MANUF TECH, V42, P180 De L, 2001, INT J PROD RES, V39, P3623 Dieterich J, 2012, APPL MATH, V3, P1552 Gao L, 2010, INT J ADV MANUF TECH, V49, P1175, DOI 10.1007/s00170-009-2449-1 Garrod W., 1990, COMPUTERS ENG ASME, V1, P139 Guo YW, 2009, ROBOT CIM-INT MANUF, V25, P280, DOI 10.1016/j.rcim.2007.12.002 HONG DS, 1995, ENG APPL ARTIF INTEL, V8, P129, DOI 10.1016/0952-1976(94)00068-X Huang HHT, 2000, J MANUF SYST, V19, P73 LEE SH, 1990, COMPUT GRAPH, V14, P237, DOI 10.1016/0097-8493(90)90035-V Li MY, 2013, INT J ADV MANUF TECH, V68, P617, DOI 10.1007/s00170-013-4782-7 Lu C, 2006, P I MECH ENG B-J ENG, V220, P255, DOI 10.1243/09544054JEM359 Marian R. M., 2003, Applied Soft Computing, V2, DOI 10.1016/S1568-4946(02)00064-9 Mello LSHD, 1990, IEEE TRAN ROB AUTO, V6, P188 MILNER JM, 1994, IEEE INT CONF ROBOT, P2058 Moore E.K, 2001, EUR J OPER RES, V135, P428 Motavalli S, 1997, COMPUT IND ENG, V32, P743, DOI 10.1016/S0360-8352(97)00014-4 Mukred J.A.A., 2012, ADV SCI LETT, V13, P732 Rashedi E, 2010, NAT COMPUT, V9, P727, DOI 10.1007/s11047-009-9175-3 Rashedi E, 2009, INFORM SCIENCES, V179, P2232, DOI 10.1016/j.ins.2009.03.004 STENTZ A, 1994, IEEE INT CONF ROBOT, P3310 Talbi E. G., 2009, METAHEURISTICS DESIG Tseng YJ, 2011, INT J ADV MANUF TECH, V57, P1183, DOI 10.1007/s00170-011-3339-x Tseng YJ, 2010, INT J ADV MANUF TECH, V48, P333, DOI 10.1007/s00170-009-2264-8 Wang JF, 2005, INT J ADV MANUF TECH, V25, P1137, DOI 10.1007/s00170-003-1952-z Zha XF, 2000, ARTIF INTELL ENG, V14, P83, DOI 10.1016/S0954-1810(99)00029-1 ZHANG WX, 1989, IEEE T SYST MAN CYB, V19, P418, DOI 10.1109/21.31045 Zhou W, 2011, INT J ADV MANUF TECH, V52, P715, DOI 10.1007/s00170-010-2738-8 Ibrahim, Ismail Ibrahim, Zuwairie Ahmad, Hamzah Jusof, Mohd Falfazli Mat Yusof, Zulkifli Md. Nawawi, Sophan Wahyudi Mubin, Marizan Engineering, Faculty /I-7935-2015 Engineering, Faculty /0000-0002-4848-7052 Ministry of Education Malaysia RDU140114; UM-UMRG - Universiti Malaya CG031-2013; High Impact Research - Ministry of Higher Education (MOHE) UM.C/HIR/MOHE/ENG/16 The authors declare that there are no conflicts of interest to disclose. This research is supported by the Ministry of Education Malaysia through the projects Fundamental Research Grant Scheme RDU140114 granted to Universiti Malaysia Pahang. This research is also partly supported by the UM-UMRG Scheme (CG031-2013) and High Impact Research UM.C/HIR/MOHE/ENG/16 granted by Universiti Malaya and Ministry of Higher Education (MOHE), respectively. 0 SPRINGER LONDON LTD LONDON INT J ADV MANUF TECH
Uncontrolled Keywords: Combinatorial optimization problem, assembly sequence planning, meta-heuristic, multi-state gravitational search algorithm, petri-net, optimization,
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 17 Mar 2016 01:29
Last Modified: 11 Oct 2018 03:03
URI: http://eprints.um.edu.my/id/eprint/15700

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