Application of simulated annealing to a linear model forthe formulation of machine cells ingroup technology

Sofianopoulou, Stella

doi:10.1080/002075497195876

Cited by 70 publications

(18 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, several studies have focused on practical attempts to overcome this limitation by speeding up the run-time without sacrificing solution quality (Chen & Srivastava, 1994;Dowsland, 1995;Sofianopoulou, 1991Sofianopoulou, , 1997. Despite the call in the literature for studies of more elaborate cooling schedules, they have materialized only slowly, in the general literature (Koulamas, Antony, & Jaen, 1994;Osman & Laporte, 1996), and are absent in the cross-docking literature.…”

Section: Background On the Methodologymentioning

confidence: 97%

An evaluation of new heuristics for the location of cross-docks distribution centers in supply chain network design

Ross

Jayaraman

2008

Computers & Industrial Engineering

View full text Add to dashboard Cite

Section: Background On the Methodologymentioning

confidence: 97%

An evaluation of new heuristics for the location of cross-docks distribution centers in supply chain network design

Ross

Jayaraman

2008

Computers & Industrial Engineering

View full text Add to dashboard Cite

“…2. To compare with Table 2 List of the GT test problems and literature references Name of test problems References of test problems GT1, GT2, GT3, GT4, GT5, GT6, GT7, GT8, GT9, GT10 Boctor (1991), Sofianopoulou (1997) GT11 Boe and Cheng (1991), Chandrasekharan and Rajagopalan (1986), Li and Parkin (1997) GT12 Boctor (1989), Burbidge (1963), Burbidge (1991), Chan and Milner (1982), Kattan (1997), Seifoddini and Wolfc (1986) GT13…”

Section: Clique Partitioning and The Gt Problemmentioning

confidence: 99%

Solving group technology problems via clique partitioning

Wang

Alidaee

Glover

et al. 2007

Int J Flex Manuf Syst

View full text Add to dashboard Cite

This paper presents a new clique partitioning (CP) model for the Group Technology (GT) problem. The new model, based on a novel 0/1 quadratic programming formulation, addresses multiple objectives in GT problems by drawing on production relationships to assign differing weights to machine/ part pairs. The use of this model, which is readily solved by a basic tabu search heuristic, is illustrated by solving 36 standard test problems from the literature. The efficiency of our new CP model is further illustrated by solving three large scale problems whose linear programming relaxations are much too large to be solved by CPLEX. An analysis of the quality of the solutions produced along with comparisons made with other models and methods highlight both the attractiveness and robustness of the proposed method.

show abstract

“…Other approaches that have been applied to the MPCF problem include simulated annealing [22,23], tabu search [24,25], GAs [26][27][28][29], GGA [30], neural networks [31] and fuzzy logic [32].…”

Section: Literature Reviewmentioning

confidence: 99%