Search Results - (( programming model optimisation algorithm ) OR ( java application customization algorithm ))

A Review of Reservoir Operation Optimisations: from Traditional Models to Metaheuristic Algorithms by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., El-Shafie A.

Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

“…In doing so, Multi-Parametric Programming technique is used to develop the computer algorithm; whereas Model-Based Predictive Control (MPC) is adopted for the design of the controller. …”
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The application of hybrid artificial intelligence techniques in the optimisation of crude palm oil production by ., Lily Amelia, Wahab, Dzuraidah, Hassan, Azmi

“…The proposed optimisation model is an integration between fuzzy expert system and multi objective programming model. …”
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Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

“…In this study, a new optimisation algorithm termed Hybrid Evolutionary-Barnacles Mating Optimisation (HEBMO) was initially formulated to solve optimisation problems. …”
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Optimising police officer schedule at Ibu Pejabat Polis Daerah (IPD) Kuala Muda using goal programming / Nurul Atikah Abdull by Abdull, Nurul Atikah

“…But it is therefore suggested that a hybrid swarm-based optimisation algorithm and a few methods be used to solve scheduling problems instead of goal programming as they provide efficiency and flexibility on the generated schedules.…”
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Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

“…To ease water scarcity, dynamic programming, stochastic dynamic programming, and heuristic algorithms have been applied to solve problem matters related to water resources. …”

A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities by Idris, A.M., Rusli, R., Nasif, M.S., Ramli, A.F., Lim, J.S.

“…The proposed risk-based model was tested using a case study involving a natural gas liquids (NGL) recovery unit, and the results were compared to a published greedy algorithm (GA) formulation. …”
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A bacteria foraging algorithm for solving integrated multi-period cell formation and subcontracting production planning in a dynamic cellular manufacturing system by Tang, Sai Hong, Nouri, Hossein, Motlagh, Omid Reza Esmaeili

“…This research aims to apply this emerging optimisation algorithm to develop a mixed-integer programming model for designing cellular manufacturing systems (CMSs), and production planning in dynamic environments. …”
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Asset liability management model: The case of selected Islamic banks in Malaysia / Chong Hui Ling by Chong , Hui Ling

“…Algorithms established for the optimisation processes are documented for the study. …”
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

“…To enhance the robustness of the algorithm, the QIEP technique is constructed based on multiobjective model in which the multiobjective functions consist of reducing power losses, increasing maximum loadability and cost minimisation. …”
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PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation by Md Zain, Badrul Aisham, Tokhi, M. Osman, Toha, Siti Fauziah

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Pembangunan model pengoptimman pengeluaran minyak sawit dan isirong sawit menggunakan pendekatan genetik kabur by ., Lily Amelia, Wahab, Dzuraidah, Hassan, Azmi

“…Model optimisation is performed using the genetic algorithm method. …”
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Development of Dynamic Programming Algorithm for Maintenance Scheduling Problem: A Conceptual Paper by Z. A. M., Fauzi, Muhamad Arifpin, Mansor

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Determining approximate Stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique by Raymond, R. Tan, Prof.

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Development of multi-objective Chaotic Immune Symbiotic Organisms Search (CISOS) algorithm for facts device installation in voltage security control / Mohamad Khairuzzaman Mohamad... by Mohamad Zamani, Mohamad Khairuzzaman

“…Comparative studies were also conducted with respect to other existing optimisation techniques namely Symbiotic Organisms Search (SOS), Particle Swarm Optimization (PSO) and Evolutionary Programming (EP). …”
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Determining optimal transportation allocation using linear programming methods / Tengku Mohd Hazimi Tuan Hassan and Maslin Masrom by Tuan Hassan, Tengku Mohd Hazimi, Masrom, Maslin

“…A case study of an operations research problem involving the optimisation of distribution costs and the effective delivery system of inventory by utilising transportation models, namely the North-West Corner Rule (NWCR), Simplex method, and Vogel's Approximation Method (VAM) are presented and discussed. …”
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Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

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Efficient task scheduling strategies using symbiotic organisms search algorithm for cloud computing environment by Sa'ad, Suleiman

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Solving a multi-period inventory routing problem with stochastic unstationary demand rates by Muhammad Khodri Harahap, Afif Zuhri

“…Thus, this research aims to develop a mathematical model known as a mixed-integer programming model to solve a multi-period stochastic unstationary inventory routing problem (MP-SUIRP) in which the demand is considered non-consistent over time. …”
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Enhanced simulated annealing for solving aggregate production planning by Abu Bakar, Mohd Rizam, Bakheet, Abdul Jabbar Khudhur, Kamil, Farah, Kalaf, Atiya, Abbas, Iraq T., Lee, Lai Soon

“…Due to the fact that aggregate production planning () is one of the most considerable problems in production planning, in this paper, we present multiobjective linear programming model for APP and optimised by . During the course of optimising for the APP problem, it uncovered that the capability of was inadequate and its performance was substandard, particularly for a sizable controlled problem with many decision variables and plenty of constraints. …”
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