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    An Optimization Model for the Maximized Profit of Housing Development Project: A Case Study of Bangkok and Perimeter, Thailand
    (2023-05-01)
    Kakaew, Siripob
    ;
    U-tapao, Chalida
    The objective of this research was to assess the profitability of the housing development project located in Bangkok, and the perimeter areas are Nonthaburi, Samut Prakan, and Pathum Thani, which are the result of good construction management. Moreover, the researchers’ previous data were used to predict the profit for construction planning, using stepwise multiple regression analysis. Then, we found the profit equation of the housing development project and applied it to the optimization model to clarify the model by the case study. The case study has 427 units, dividing the house into three types, with an optimization performed using the GAMS tool. In the same way, according to this optimization, it can be divided into two scenarios: scenario one found the maximized profit of the project to be 1053.91 MB, and scenario two was the result of making a sensitive analysis of scenario one and found the maximized profit of the project to be 1054.18 MB, which is the best scenario for the maximized profit of the project, and so it is the best choice for construction planning. The research contribution in this model can be applied to other projects that are suitable for large or densely populated cities, such as Beijing, New Delhi, and others. In the Conclusion section, we offer recommendations and detail future work that the researchers have discussed and described for the benefit of future research in housing development projects.
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    Optimizing Distribution Network Models for a Fruit Trading Company in Thailand: A Comparative Study Using Linear Programming and Optimization
    (2023-01-01)
    Akkawuttiwanich, P.
    ;
    Yenradee, P.
    ;
    Horng, S.
    ;
    Pichpibul, T.
    This research investigates the distribution network model of a fruit trading company in Thailand, with a specific focus on the problem of excessive travel distances and vehicle requirements in the company's existing distribution system. Linear programming and optimization techniques are used to improve the distribution network model and to satisfy the daily demand. Results are compared between the current distribution scenario and the optimized model. The computational analysis reveals a significant 21.8% reduction (802 kilometers) in total traveling distance and a 33.33% decrease in the number of vehicles required. Additionally, a comprehensive cost analysis is proposed, incorporating fuel costs, CO2 emissions, and overtime expenses, which were previously overlooked. This research offers valuable insights into the potential benefits of optimization, including cost savings and environmental impact reduction, providing a practical template for managing distribution networks, reducing reliance on ad hoc practices, and fostering a sustainable business model to enhance competitiveness in a challenging market.
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    Optimal multi-path energy-aware routing protocol for wireless sensor networks
    (2012-10-02)
    Tanessakulwattana, Sarayoot
    ;
    Pornavalai, Chotipat
    ;
    Chakraborty, Goutam
    ;
    Naik, Sagar
    A large portion of energy-aware routing protocol for wireless sensor networks are cluster-based. In cluster based approaches, power of the cluster head (CH) nodes are drained more rapidly compared to other member nodes. Dynamic CH approach could partially alleviate this problem. But even with dynamic CH approach, energy is not uniformly dissipated among all nodes. In this paper, we propose a new energy-aware routing protocol where the communication protocol is such that, even when the clusters are fixed, power dissipation is same over all nodes (except CHs). Every node co-operates with each other to carry the payload to the CH so as the power dissipation is uniform. Therefore reconfiguration of cluster is not necessary, thereby saving a huge signalling cost and interruption in service. Simulation results show that the proposed protocol has longer node lifetime and better distribution of energy dissipation than the original LEACH protocol. © 2012 IEEE.
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