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 Methods
.: Available Methods
The following methods are installed for solution assignment.
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ID TYPE NAME DESCRIPTION NO. OF
SOLUTIONS
BEST SOLUTIONS
APD help TMS help DPD help
20 D ABMPSRT   hueristic 25 0 1 1
16 C AB_ACS   submitted by Ameisenbär, (2011) 135 0 0 0
17 C AB_CACS   submitted by Ameisenbär, (2011) 4 0 0 0
19 C AB_CMACS   submitted by Ameisenbär, (2011) 82 0 0 0
18 C AB_MACS   submitted by Ameisenbär, (2011) 13 0 0 0
34 C ACO   Metaheuristic Optimizations. 19 0 0 0
1 D CMAS/ES   Multi-Agent System, which uses a coordination mechanism based on evolutionary search; submitted by Homberger, J., (2008), OR-Spectrum. 460 5 26 19
7 D CMAS/ES-BORDA   Multi-Agent System, which uses a coordination mechanism based on evolutionary search and borda voting; not submitted so far; developed by Birkner, C.; Homberger, J. 283 0 3 29
6 D CMAS/ES-STV   Multi-Agent System, which uses a coordination mechanism based on evolutionary search and single transfer voting; not submitted so far; developed by Dietz, C.; Wurster, C.; Homberger, J. 206 1 5 4
9 D CMAS/PROP-STV   Multi-Agent System, which uses a coordination mechanism based on ant system and single transfer voting; not submitted so far; developed by Dietz, C.; Homberger, J. 38 0 0 0
2 D CMAS/SA   Multi-Agent System, which uses the coordination mechanism of Klein (2003) and Fink (2004); submitted by Homberger, J., (2008), OR-Spectrum. 204 0 1 5
24 C EDDF   Earliest due date first 1 0 0 0
23 C FCFS   First come first served with parallel SGS 2 0 0 1
15 C Fwd/Bwd   Multi-pass (Forward-Backward) approach using Serial Schedule Generation Scheme (S-SGS). Approach adapted from "Iterative forward-backward approach" by Li and Willis (1992) 8 0 0 0
22 C GA-RK   Genetic Algorithm with random keys coding, binary tournament, 2-point crossover, standard mutation and elitism. 18 0 3 2
11 D GA-RR/1/B   Genetic Algorithm Round Robin One-Point-Crossover Borda 23 0 0 4
33 C GA_WS   Genetic Algorithm with individual calculation of priority rules, normalized with weighted sum function 56 0 24 17
14 D GT-MAS   A Game Theoretic Approach to Decentralized Multi-Project Scheduling; submitted (2009), by T.Wauters, K. Verbeeck, G. Vanden Berghe and P. De Causmaecker 162 25 3 3
13 C HYPER   Hyperheuristic search 34 4 2 1
10 H MAS/CG   Multi-Agent System, which is based on decentral problem solving using a column generation mechanism; not implemented so far. 0 0 0 0
5 H MAS/CI   Mult-Agent System, which uses a central imposing coordination mechanism (information asymmetry is not considered); published by Homberger, J., (2007), International Transactions in Operational Research 14(6), 565-589. 140 0 0 0
8 D MAS/PS   Multi-Agent System, which uses a coordination mechanism based on different priority rules and voting rules; not submitted so far; developed by Trautmann, H.; Homberger, J. 315 1 1 2
31 D MAS_EVO_DE   Multi Agent System which uses a coordination mechanism based on evolutionary search and exponential or linear declining number of possible solutions each round. (DHBW - WWI2011E) 197 0 0 0
29 H MATHEUR   Matheuristic based on our MISTA 2013 Challenge algorithm. (2013) 118 98 23 9
21 C MILP   Model solved by a MILP solver. 0 0 0 0
26 C MINLFT   Minimum latest finish time 1 0 0 0
27 C MINSLK   Minimum slack 2 0 0 0
28 C MINTWK   Minimum total work content 1 0 1 0
32 C MRR   Max required Resources = Highest Job Priority 1 0 0 0
30 C PSGSMINSLK   PR-based heuristic with a Parallel Schedule Generation Scheme (P-SGS) and Minimum Activity (Total) Slack First (MIN-SLK) as Priority Rule (PR) 485 0 16 29
3 C RES   Evolutionary Metaheuristic (information asymmetry is not considered); published by Homberger, J., (2007), International Transactions in Operational Research 14(6), 565-589. 218 2 28 10
12 C RLS   Repeated Local Search 438 0 0 3
4 C SASP   Priority rule based heuristic of Lova and Tormos (2001) (information asymmetry is not considered); submitted by Homberger, J., (2008), OR-Spectrum. 190 0 0 0
25 C WACRU   weighted activity criticality & resource utilization 1 0 0 0