Indexed Journal Papers 2018

Indexed Journal Papers 2018

  • Optimizing a Just-In-Time logistics network problem under fuzzy supply and demand: two parameter-tuned metaheuristics algorithms. Memari, A. Ahmad R., Rahim, A. R. A., Hassan, A. Neural Computing and Applications, Vol. 30 (10). Pp 3221 – 3233. Q1. IF 4.213

Just-In-Time (JIT) is a popular philosophy in many industrial practices. The concept of JIT in early studies concerned with improving operational efficiency and waste minimization. In recent decades, however, JIT principles have also connected to logistics efficiency particularly for distribution of raw materials and finished goods. In the literature, several attempts have been made to optimize JIT logistics networks. On the one hand, most studies have typically focused on deterministic and small-scale problems which have been solved by exact algorithms. On the other hand, when large-scale problems were considered and usually were solved by metaheuristics algorithms, uncertainty sources and fine-tuning of the metaheuristics parameters were generally ignored. In this paper, we develop a mixed-integer linear optimization model to investigate a large-scale JIT logistics problem with 15 different sizes. To deal with different uncertainty sources, the customers demand and suppliers’ capacity as the two main sources of uncertainty in practice are considered as triangular fuzzy parameters. The proposed model aims to minimize total logistics cost including costs of transportation, inventory holding and backorders. A particle swarm optimization algorithm is applied to solve the problem, and its results are then validated by a harmony search algorithm. Both algorithms parameters are tuned using response surface methodology and Taguchi method. Finally, the conclusion and some directions for future research are proposed.

Evapotranspiration is the combination of evaporation and transpiration processes that give means the process of water loss to the atmosphere. Reference evapotranspiration (ETo) estimation is part of water cycle that importance for planning and management of irrigation purposes and water resource systems. Due to its importance, the accurate modeling of ETo is of vital importance to estimate crop water requirement and its availability. This research presents a system identification and differential evolution approach by using Differential Evolution and System Identification (DESI) and Modified Genetic Algorithm (MGA) approach for modeling daily and monthly ETo in peninsular of Malaysia. The data set comprising air temperature, humidity, wind speed, and solar radiation was utilized for estimating ETo using FAO56 Penman Monteith (PM) equation as the reference. The modeling results were analyzed and compared with the traditional Penman Monteith method. Based on the analyses, the approach used was found that the models of ETo is adequate and understandable, and suited to estimate the dynamics of the evapotranspiration process. The performance of the model is comparable with that of the PM method.

Multi-objective optimization differential evolution (MOODE) algorithm has demonstrated to be an effective algorithm for selecting the structure of nonlinear auto-regressive with exogeneous input (NARX) model in dynamic system modeling. This paper presents the expansion of the MOODE algorithm to obtain an adequate and parsimonious nonlinear auto-regressive moving average with exogenous input (NARMAX) model. A simple methodology for developing the MOODE-NARMAX model is proposed. Two objective functions were considered in the algorithm for optimization; minimizing the number of term of a model structure and minimizing the mean square error between actual and predicted outputs. Two simulated systems and two real systems data were considered for testing the effectiveness of the algorithm. Model validity tests were applied to the set of solutions called the Pareto-optimal set that was generated from the MOODE algorithm in order to select an optimal model. The results show that the MOODE-NARMAX algorithm is able to correctly identify the simulated examples and adequately model real data structures.

Application of piezoelectric fan in electronic cooling system has been proven that it is more efficient than natural convection with least power consumption and has high potential to replace existing rotary fan for its simplicity and longer life. An integration of piezoelectric fan with magnet is to widen the cooling coverage area with similar power consumption and cost of running a single piezoelectric fan. By optimizing the repulsive magnetic force generated in between the magnets, the overall fans oscillate with significant average amplitude. The purpose of this paper is to investigate the performance of multiple piezoelectric-magnetic fan and its significance in reducing temperature while enhance the heat transfer. The parameters under investigation are the distance between magnets and fans orientation. In this study four magnetic fans were activated by a piezoelectric fan.  It is found that at distance between magnets is 14 millimeters; the average amplitude is largest at highest resonant frequency. The multiple fans is better to be arranged in radial orientation for its ability to produce larger repulsive magnetic force to oscillate the adjacent fans. The distribution of repulsive magnetic force in radial orientation is five times better than array orientation. Therefore, radial piezoelectric-magnetic fan (RPMF) produces larger average amplitude of fans which is 111%. 30% of power consumption per unit coverage area is secured. RPMF generates average wind velocity of 0.4m/s compared to array orientation 0.17m/s.

Biomass residues due to their low bulk density typically require frequent transportation from biomass plantations in rural areas to conversion bio-energy power plants. This issue contrasts with environmental protection strategies, especially when power plants are facing different carbon reduction policies that enforce them to emit less than a given specific carbon amount. Although several researchers have investigated bio-energy supply chains concerning environmental policies, the majority of studies have been devoted to strategic decisions over a single planning period. This paper presents a multi-period bio-energy supply chain under carbon pricing (carbon tax) and carbon trading (cap-and-trade) policies at the tactical planning level. A mixed-integer linear programming model was adopted to optimize the proposed regional oil-palm biomass-to-bio-energy supply chain planning model. The numerical results indicate that when carbon pricing is in place when carbon tax increases linearly, carbon emissions’ reductions have a nonlinear trend, whereas both cost increase and carbon emissions’ reductions have a relatively upward trend in the carbon trading scheme. This paper also presents the sensitivity analysis of the proposed model regarding cost, emissions’ generation and supply chain performance. Finally, the paper recommends several significant practical implications and policy-making insights for managers and policymakers.

Recently, piezoelectric fan has gained attention as potential active cooling method for electronics devices. Even though the piezoelectric requires high voltage, there are findings to overcome the shortcomings. Adding on a magnet at the tip of the piezoelectric fan to activate other magnetic passive fans is one of the methods to increase the total amplitude generated by the fans. This paper will discuss on the performance of integrated piezoelectric fan with passive fans (later refer to magnetic fans) to enhance the heat transfer in cooling system. A repulsive force produced by the magnets will cause the magnetic blades to oscillate together with the piezoelectric fan. The paper will focus on the optimization parameters of the magnets for selected dimension of piezoelectric fan. The parameters under investigation are the position of the magnet on the piezoelectric fan, number of magnets on each blades and orientation of blades with respect to adjacent blade. Results show that the magnet at middle location of extensive blade with double magnets generate the largest amplitude, 80% better than fan without magnet and for dual integrated piezoelectric fan with magnetic fan, radial orientation gives better result by 25%. By increasing the total amplitude using magnetic force, power consumption can be reduced while the heat transfer performance can be enhanced. it shows a good agreement for positive heat transfer and thermal resistance improvement compared to natural convection.

Energy harvesting (EH) module for wireless sensor network has become a promising feature to prolong the conventional battery inside the devices. This emerging technology is gaining interest from sensor manufacturers as well as academicians across the globe. The concept of employing EH module must be cost effective and practical. In such, the use of EH module type besides RF is more realistic due to the size of the scavenger module, the availability of the resources and conversion efficiency. Most of the oil and gas plants have some drawbacks in scavenging RF from surrounding (i.e. router, Wi-Fi, base station, cell phone) due to its placement in remote area and thus limited energy sources could be a threat in this application. Multiple sources, including co-channel interference (CCI) in any constraint nodes is a feasible way of scavenging several wastes from ambient RF energy via wireless mesh topology. In this paper, a 3-node decode-and-forward (DF) model is proposed where the relay node is subject to an energy constraint. Multiple primary sources and CCI are added in the system model known as Multiple-Source and Single-Relay (MSSR). A mathematical model is derived in Time Switching Relaying (TSR) and Power Splitting Relaying (PSR) schemes to obtain an average system throughput at a destination. Numerical simulation with respect to the average throughput and EH ratio was performed and compared with the Single-Source and Single-Relay (SSSR) and ideal receiver. By applying multiple sources and CCI as an energy enhancement at the constraint node, the optimal value of EH ratio for TSR can be reduced significantly by 10% as compared to the ideal receiver whereas the optimal value of EH ratio for PSR is outweigh TSR in terms of overall system throughput.

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