https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34322 Wed 27 Feb 2019 12:32:14 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30426 Wed 23 Jan 2019 11:51:21 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:9258 Wed 11 Apr 2018 12:50:21 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34298 Tue 26 Feb 2019 14:15:13 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:45983 Tue 08 Nov 2022 14:33:24 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:40971 Thu 21 Jul 2022 08:45:23 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:48535 Diagnostic and Statistical Manuals of Mental Disorders “DSM-IV” and the most recent addition, DSM-5 allow us to introspect, using the solution provided by modern algorithms, if there exists a consensus between the clusters obtained via a data-driven approach, with the current classifications. In the case of mental disorders, the availability of a follow-up consensus collection (e.g. in this case the DSM-5), potentially allows investigating if the classification of disorders has moved closer (or away) to what a data-driven analytic approach would have unveiled by objectively inferring it from the data of DSM-IV. In this contribution, we present a new type of mathematical approach based on a global cohesion score which we introduce for the first time for the identification of communities of symptoms. Different from other approaches, this combinatorial optimization method is based on the identification of “triangles” in the network; these triads are the building block of feedback loops that can exist between groups of symptoms. We used a memetic algorithm to obtain a collection of highly connected-cohesive sets of symptoms and we compare the resulting community structure with the classification of disorders present in the DSM-IV.]]> Thu 02 May 2024 14:32:58 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:1491 Sat 24 Mar 2018 08:28:05 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:17467 Sat 24 Mar 2018 08:04:12 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18758 Sat 24 Mar 2018 08:02:46 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29215 Sat 24 Mar 2018 07:36:46 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:3893 Sat 24 Mar 2018 07:22:42 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:3851 Sat 24 Mar 2018 07:19:57 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:22173 max. In the permutational scenario, the sequence of jobs has to remain the same in all machines. The Flowshop Problem (FSP) is known to be NP-hard when more than three machines are considered. Thus, for medium and large scale instances, high-quality heuristics are needed to find good solutions in reasonable time. We propose and analyse parallel hybrid search methods that fully use the computational power of current multi-core machines. The parallel methods combine a memetic algorithm (MA) and several iterated greedy algorithms (IG) running concurrently. Two test scenarios were included, with short and long CPU times. The tests were conducted on the set of benchmark instances introduced by Taillard (Eur. J. Oper. Res. 64:278–285, 1993), commonly used to assess the performance of new methods. Results indicate that the use of the MA to manage a pool of solutions is highly effective, allowing the improvement of the best known upper bound for one of the instances.]]> Sat 24 Mar 2018 07:14:59 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23348 NP-hardness, research has focused on approximate methods like metaheuristics. Tabu Search (TS) is a very efficient metaheuristic for combinatorial problems. We investigate four different versions of TS with different tabu objects and compare them to the Lin-Kernighan (LK) heuristic as well as the recently developed Multi-Neighborhood Search (MNS). LK is currently considered to be the best approach for solving the TSP, while MNS has shown to be highly competitive. We then propose new hybrid algorithms by hybridizing TS with Evolutionary Algorithms and Ant Colony Optimization. These hybrids are compared to similar hybrids based on LK and MNS. This paper presents the first statistically sound and comprehensive comparison taking the entire optimization processes of (hybrid) TS, LK, and MNS into consideration based on a large-scale experimental study. We show that our new hybrid TS algorithms are highly efficient and comparable to the state-of-the-art algorithms along this line of research.]]> Sat 24 Mar 2018 07:13:33 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27544 Mon 30 Apr 2018 14:39:48 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:33153 Mon 23 Sep 2019 10:41:03 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:42782 Fri 02 Sep 2022 12:24:36 AEST ]]>