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Meta-heuristic structure for multiobjective optimization case study: Green sand mould system by Ganesan, T., Elamvazuthi, I., KuShaari, K.Z., Vasant, P.

“…Analysis on the solution set produced by these algorithms is carried out using performance metrics. …”
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Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation by Choong, Shin Siang

“…Approximation algorithm is a sub-class of techniques which is able to provide sub-optimal solution(s) with reasonable computational cost. …”
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Normal-boundary intersection based parametric multi-objective optimization of green sand mould system by Ganesan, T., Vasant, P., Elamvazuthi, I.

“…Thus, it is crucial for the engineer to have access to multiple solution choices before selecting of the best solution. …”
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Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

“…A Genetic Algorithm is successful in generating near -optimal solutions if it is able to produce o®spring during crossover that is better than the parent solutions. …”
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

“…Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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CPU Burst Processes Prioritization Using Priority Dynamic Quantum Time Algorithm: A Comparison with Varying Time Quantum and Round Robin Algorithms by Mohammed, Maysoon A., Mazlina, Abdul Majid, Balsam, A. Mustafa, Ghani, Rana Fareed

“…The choice of the quantum time in RR is the optimal solution for the problem of large turnaround and waiting time with RR. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Scheduling scientific workflow in multi-cloud: a multi-objective minimum weight optimization decision-making approach by Farid, Mazen, Heng, Siong Lim, Chin, Poo Lee, Latip, Rohaya

“…In particular, we use particle swarm optimization (PSO) to expand the FR-MOS multi-objective scheduling algorithm by using fuzzy resource management to maximize variety and obtain optimal Pareto convergence. …”
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Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms by Teo, Jason Tze Wi, Johnny Koh, Chin, Kim On, Chua, Bih Lii, Willey Liew, Noor Ajian Mohd. Lair, Lim, Shun Hoe

“…The research continues by transferring the evolved solutions from simulation to the real world using 30 printing. …”
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An improved simulated annealing algorithm to avoid crosstalk in optical omega network by Abdullah, Monir, Othman, Mohamed, Johari, Rozita

“…It is a good idea to use these two algorithms to improve the performance. …”
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Modified Genetic Algorithm To Determine The Location Of The Distribution Power Supply Networks In The City by Fedorchenko, Ievgen, Andrii, Oliinyk, Jamil Alsayaydeh, Jamil Abedalrahim, Kharchenko, Anastasia, Stepanenko, Aleksandr, Shkarupylo, Vadym

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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan Yin Keong, Tan Yin

“…The solution obtained from the LB–MILP model, i.e., the decision variables (binary variables), was used to obtain a feasible solution for model UB–NLP. …”
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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan , Yin Keong

“…The solution obtained from the LB-MILP model, i.e., the decision variables (binary variables), was used to obtain a feasible solution for model UB-NLP. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering by Rashed, Alwatben Batoul

“…One characteristic of MOPSO with Pareto optimality scheme is associated with selection mechanism for archive update. However, the PSO algorithm produces a group of non-dominated solutions which makes the choice of a “suitable” Pareto optimal or non-dominated solution more difficult. …”
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MYMealPal: Malaysian healthy meal planner using artificial bee colony approach / Wan Muhamad Amirul Hakimi Wan Mohd Zaki by Wan Mohd Zaki, Wan Muhamad Amirul Hakimi

“…Harris-Benedict equation is used in finding the calorie needed for a user in a day. …”
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Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin by Baharuddin, Ramizah

“…In Newton’s method, approximation is done by using tangential lines. The solution process begins with choosing a value as the first estimate of the solution (normally obtained from graphing). …”
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Optimised combinatorial control strategy for active anti-roll bar system for ground vehicle by Zulkarnain, N., Zamzuri, H., Saruchi, S. A., Hussain, A., Mokri, S. S., Jedi, A., Razali, N., Mohd Nordin, I. N. A.

“…From the application point of view, both tuning process can be used. However, using optimisation method gives a multiple choice of solutions and provides the optimal parameters compared to manual tuning method.…”
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An enhanced soft set data reduction using decision partition order technique by Mohammed, Mohammed Adam Taheir

“…Also, the accuracy of original soft-set optimal and sub-optimal results have been improved using an intelligent SSR-BPSO-BBO algorithm. The computational cost of search domain (space) has been enhanced using proposed Markov Chain Model.…”
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African Buffalo Optimization and the Randomized Insertion Algorithm for the Asymmetric Travelling Salesman’s Problems by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad, Odili, Esther Abiodun

“…Our interest in the asymmetric Travelling Salesman’s Problem (ATSP) is borne out of the fact that most practical daily-life problems are asymmetric rather than symmetric. The choice of the Random Insertion Algorithm as a comparative algorithm was informed by our desire to investigate the general belief among the scientific community that Heuristics being mostly problem-dependent algorithms are more efficient that metaheuristics that are usually general-purpose algorithms. …”
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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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