Indexed Journal papers 2019

The Internet of Things (IoT) has been integrated in various applications such as smart homes and smart cities. IoT in agriculture such as in monitoring indoor climatic conditions can help to improve the plant growth. This paper proposes a new approach in utilizing IoT technology as a remote monitoring system to control the indoor climatic conditions via light emitting diode (LED) parameters which include spectrums, photoperiod and intensity in order to increase yields as well as to reduce the turnaround time. This study showed that growth of Brassica chinensisunder different wavelengths of light source has influenced plant growth performance and phytochemicals characteristics. Four different light treatments were experimented using pulse treatment (1 h light and 1 h dark), continuous light (CL), high intensity and artificial light control of 12 h light and 12 h dark. Data such as the leaves count, height, dry weight and chlorophyll a & b of plants were analyzed. The results showed high mean value of plants’ fresh weight (FW) of 410.77 g under pulse treatment compared to other light treatments. The percentage of moisture content (MC) was recorded higher on average under normal light (99.15%), value of leaf area (LA) was recorded higher under artificial sunlight with an average value of 976.84 cm². Even though the results of LA were better under artificial sunlight, CL with low intensity gave higher stem height (SH) and number of leaves (NOL). In order to capture real-time data and monitor the environmental parameters of the plant experiment, an intelligent embedded system was developed to automate the LED control and manipulation. The results showed that the system is stable and has significant referential in the area of plant factory or indoor farming.

• A New Modified Firefly Algorithm for Optimizing a Supply Chain Network Problem. Ashkan Memari, Robiah Ahmad, Mohammad Reza Akbari Jokar and Abd. Rahman Abdul Rahim. Appl. Sci. 2019, 9(1), 7; https://doi.org/10.3390/app9010007

Firefly algorithm is among the nature-inspired optimization algorithms. The standard firefly algorithm has been successfully applied to many engineering problems. However, this algorithm might be stuck in stagnation (the solutions do not enhance anymore) or possibly fall in premature convergence (fall into the local optimum) in searching space. It seems that both issues could be connected to exploitation and exploration. Excessive exploitation leads to premature convergence, while excessive exploration slows down the convergence. In this study, the classical firefly algorithm is modified such that make a balance between exploitation and exploration. The purposed modified algorithm ranks and sorts the initial solutions. Next, the operators named insertion, swap and reversion are utilized to search the neighbourhood of solutions in the second group, in which all these operators are chosen randomly. After that, the acquired solutions combined with the first group and the firefly algorithm finds the new potential solutions. A multi-echelon supply chain network problem is chosen to investigate the decisions associated with the distribution of multiple products that are delivered through multiple distribution centres and retailers and demonstrate the efficiency of the proposed algorithm. View Full-Text

• Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. A Memari, A Dargi, MRA Jokar, R Ahmad, ARA Rahim. Journal of Manufacturing Systems 50, 9-24

The concept of sustainability is becoming an essential philosophy for numerous industrial sectors because of the increase in environmental protection and social obligations awareness. A sustainable supplier selection is the first step towards this trend. It is also a challenging problem since multi-criteria group decision-making is engaged with numerous conflicting requirements in which decision makers’ knowledge is commonly imprecise and vague. This research presents an intuitionistic fuzzy TOPSIS method to select the right sustainable supplier that concerns nine criteria and thirty sub-criteria for an automotive spare parts manufacturer. The proposed approach provides an accurate sustainable ranking of suppliers and a reliable solution for sustainable sourcing decisions that is validated through a real-world case study. This paper ends with research and theoretical findings, managerial insights and directions for future research.