A software framework for fast prototyping of meta‐heuristics hybridization

Lau, Hoong Chuin; Wan, Wee Chong; Halim, Steven; Toh, Kaiyang

doi:10.1111/j.1475-3995.2007.00578.x

Cited by 11 publications

(15 citation statements)

References 20 publications

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“…Pseudo-code is a code that can be read easily by humans, but it is not a computer programming language. Currently, there exists modelling type programming languages in meta-heuristics domain for instances MDF [10] and ParadisEO [11]. The modelling language is considered as a computer programming language if it has an automatic translator that converts the modelling codes into an executable computer codes.…”

Section: 51computer Programming Languagementioning

confidence: 99%

Software framework for optimization problems and meta-heuristics based on scripting language

Masrom¹,

Abidin

Omar

et al. 2018

J. Fundam and Appl Sci.

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Since most researchers working algorithm for their specific optimization problem, the task of selecting, modifying and extending codes from rapid software framework is very likely to occur. Software framework enables design and codes reuse meta-heuristics. This paper presents a review of the available meta-heuristics and summarize some important fea about a new software framework based on scripting language is given. Furthermore, the Since most researchers working in meta-heuristics fields are required to develop their own algorithm for their specific optimization problem, the task of selecting, modifying and extending codes from rapid software framework is very likely to occur. Software framework codes reuses to allow faster programming development of the paper presents a review of the available rapid software framework for heuristics and summarize some important features of the rapid software. A software framework based on scripting language is given. Furthermore, the scripting language that was used to develop a meta-heuristics algorithm of PSO hybridization is evaluated according to the conciseness aspects. This results program codes with scripting language has more conciseness that the main oftware

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Section: 51computer Programming Languagementioning

confidence: 99%

Software framework for optimization problems and meta-heuristics based on scripting language

Masrom¹,

Abidin

Omar

et al. 2018

J. Fundam and Appl Sci.

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“…It has been shown from a comparative study that LTH method has sparked the most interest among researchers compared to other schemes [14]. In term of the algorithm effectiveness, LTH has been proved to outperform LRH and HRH [19].…”

Section: Low-level Teamwork Hybridization (Lth)mentioning

confidence: 99%

Low-level Teamwork Hybridization for P-metaheuristics: A review and comparison

Masrom

Abidin

Hashimah

et al. 2011

2011 3rd Conference on Data Mining and Optimization (DMO)

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Inspired by nature, many types of Population based metaheuristics or P-metaheuristics is cropping out of research labs to help solve real life problems. Since every metaheuristics has its own strength and weaknesses, hybridizing the algorithms can sometimes produce better results. To this date of literature, Low-level Teamwork Hybridization is considered as an effective and popular method for hybridization of P-metaheuristics. In many cases however, the approach might prove to be quite complicated.The hybridization often requires metaheuristics internal structure modification in order for the different algorithms to fit well together. Another difficulty is in determining which strategies to be retained and which to be dropped or replaced in each of the metaheuristic algorithms. This paper provides a general abstraction for P-metaheuristics and describes the main Pmetaheuristics components that are suitable candidates for hybridization. The review and comparative study of several implementations of Low-level Teamwork Hybridization is also presented. (Abstract)

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“…The off-line mode uses log files which makes it easy to be interfaced with virtually any local search implementation, e.g. COMET [19], MDF [14], etc.…”

Section: Using Vizmentioning

confidence: 99%

Viz

Halim

Yap

Lau

2006

Proceedings of the 19th Annual ACM Symposium on User Interface Software and Technology

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N P-hard combinatorial optimization problems are common in real life. Due to their intractability, local search algorithms are often used to solve such problems. Since these algorithms are heuristic-based, it is hard to understand how to improve or tune them. We propose an interactive visualization tool, VIZ, meant for understanding the behavior of local search. VIZ uses animation of abstract search trajectories with other visualizations which are also animated in a VCR-like fashion to graphically playback the algorithm behavior. It combines generic visualizations applicable on arbitrary algorithms with algorithm and problem specific visualizations. We use a variety of techniques such as alpha blending to reduce visual clutter and to smooth animation, highlights and shading, automatically generated index points for playback, and visual comparison of two algorithms. The use of multiple viewpoints can be an effective way of understanding search behavior and highlight algorithm behavior which might otherwise be hidden.

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A software framework for fast prototyping of meta‐heuristics hybridization

Cited by 11 publications

References 20 publications

Software framework for optimization problems and meta-heuristics based on scripting language

Software framework for optimization problems and meta-heuristics based on scripting language

Low-level Teamwork Hybridization for P-metaheuristics: A review and comparison

Viz

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