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EXPERIMENTAL VALIDATIONTable of Contents:
To estimate the quality of a route and processing efficiency of HFMPSO algorithm, various types of experiments were carried out. The practical logistics data have been gathered from a logistic industry in Chennai as well as the collection of two cities named Pondicherry and Kanchipuram are selected for experimental dataset. TABLE 2.2 Logistic Cost Analysis of Different Models under Varying Number of Packages (Pondicherry)
Performance Analysis under Varying Package CountTable 2.2 and Figure 2.3 illustrate the logistic cost prediction of different methods in a varying number of packages between Chennai and Pondicherry. It is depicted that the proposed method obtains higher logistic cost when compared with alternative techniques. With respect to total of 150 packages, it is implied that the presented system attains greater logistic cost of 7700, while the FDLP and ILSP approaches reached a minimum logistic cost of 4590 and 5140, respectively Simultaneously by using the package value of 200, the FDLP model has provided a lower logistic cost of 4830 and the ILSP method achieved a better logistic cost of 5240. Flowever, the projected system displays slightly better outcome by reaching a higher logistic cost of 7890. Likewise, by applying the package number of 250, the deployed method shows a maximum logistic value of 8000 and FDLP and ILSP frameworks attained a less logistic cost of 5030 and 5600, respectively In the same way, using the package number of 300, it is demonstrated that the proposed system has shown productive results by reaching higher logistic cost of 8190, while the FDLP and ILSP technologies accomplish a minimum logistic cost of 5182 and 6000, respectively FIGURE 2.3 Logistic cost analysis of different models under varying number of packages (Pondicherry). TABLE 2.3 Logistic Cost Analysis of Different Models under Varying Number of Packages (Kanchipuram)
Table 2.3 and Figure 2.4 show the logistic cost analysis of diverse models under a varying number of packages between Chennai and Kanchipuram. It is shown that the HFMPSO model attains maximum logistic cost over the other models. Under a total of 150 packages, it is shown that the HFMPSO model achieves a maximum logistic cost of 8356, whereas the FDLP and ILSP models obtained a lower logistic cost of 4748 and 5026, respectively. At the same time, under the package count of 200, the FDLP model has offered a minimum logistic cost of 5047 and the ILSP model has reached to a slightly higher logistic cost of 5737. But the HFMPSO model shows better results by achieving a maximum logistic cost of 8552. Similarly, under the package count of 250, the HFMPSO model exhibits a higher logistic count of 8713, whereas the FDLP and ILSP models reached to a minimum logistic cost of 5300 and 5783, respectively. Likewise, under the package count of 300, it is exhibited that the HFMPSO model has demonstrated effective results by attaining a maximum logistic cost of 8920, whereas the FDLP and ILSP models obtained a lower logistic cost of 5541 and 6185, respectively. Performance Analysis under Varying Vehicle CapacitiesTable 2.4 and Figure 2.5 illustrate the logistic cost prediction of different methods in a varying number of vehicles between Chennai and Pondicherry. It is depicted that the proposed FIGURE 2.4 Logistic cost analysis of different models under varying number of packages (Kanchipuram). TABLE 2.4 Logistic Cost Analysis of Different Models under Varying Vehicle Capacities (Pondicherry)
method obtains higher logistic cost when compared with alternative techniques. With respect to total of 150 vehicles, it is implied that the presented system attains greater logistic cost of 7780, while the FDLP and ILSP approaches reached a minimum logistic cost of 4890 and 5430, respectively. Simultaneously, by using the vehicle count of 200, the FDLP model has provided a lower logistic cost of 4820 and the ILSP method achieved a better logistic cost of 5380. However, the projected system displays slightly better outcome by reaching a higher logistic cost of 7800. Likewise, by applying the vehicle capacity of 250, the deployed method shows a maximum logistic value of 7900 and FDLP and ILSP frameworks attained a less logistic cost of4830 and 5360, respectively. In the same way, using the vehicle capacity of 300, it is demonstrated that the proposed system has shown productive results by reaching higher logistic cost of 7938, while the FDLP and ILSP technologies accomplish a minimum logistic cost of 4810 and 5370, respectively. Finally, under the vehicle capacity of 350, it is shown that the HFMPSO model reaches a maximum logistic cost of 8030, whereas the FDLP and ILSP models have attained a lower logistic cost of 4810 and 5370, respectively. Table 2.5 and Figure 2.6 show the logistic cost analysis of diverse models under a varying number of vehicle capacity between Chennai and Kanchipuram. It is shown that the HFMPSO model attains maximum logistic cost over the other models. Under a total of FIGURE 2.5 Logistic cost analysis of different models under varying vehicle capacities (Pondicherry). TABLE 2.5 Logistic Cost Analysis of Different Models under Varying Vehicle Capacities (Kanchipuram)
150 vehicle capacities, it is shown that the HFMPSO model achieves a maximum logistic cost of 7778, whereas the FDLP and ILSP models obtain a lower logistic cost of 4870 and 5000, respectively. At the same time, under the vehicle capacity of 200, the FDLP model has offered a minimum logistic cost of 4810 and the ILSP model has reached a slightly higher logistic cost of 5550. But, the HFMPSO model shows better results by achieving a maximum logistic cost of 7810. Similarly, under the vehicle capacity of 250, the HFMPSO model exhibits a higher logistic count of 7890, whereas the FDLP and ILSP models reached a minimum logistic cost of 4820 and 5390, respectively. Likewise, under the vehicle capacity of 300, it is exhibited that the HFMPSO model has demonstrated effective results by attaining a maximum logistic cost of 7920, whereas the FDLP and ILSP models obtain a lower logistic cost of 4820 and 5378, respectively. Besides, under the vehicle capacity of 350, the HFMPSO model has demonstrated effective results by attaining a maximum logistic cost of 7400, whereas the FDLP and ILSP models obtained a lower logistic cost of 4810 and 5360, respectively. Computation Time (CT) analysisFigure 2.7 shows the CT analysis of diverse models under a varying number of packages from a transmit between Chennai and Pondicherry. It is shown that the HFMPSO model FIGURE 2.6 Logistic cost analysis of different models under varying vehicle capacities (Kanchipuram). FIGURE 2.7 CT analysis under varying package count (Pondicherry). requires minimum CT over the compared methods. For instance, under the presence of 150 packages, the HFMPSO model requires a minimum CT of 80 ms, whereas the existing FDLP and ILSP models need a maximum CT of 3000 and 3162 ms, respectively. On the other side, under the maximum package count of 300, it is noted that the HFMPSO model offers a least CT of 10^{5} ms, whereas the existing FLDP and ILSP models have offered a maximum CT of 10^{s} ms. Figure 2.8 examines the CT offered by diverse models under a varying number of packages from a transmit between Chennai and Kanchipuram. It is evident that the HFMPSO FIGURE 2.8 CT analysis under varying package count (Kanchipuram). model requires minimum CT over the compared methods. For instance, under the presence of 150 packages, the HFMPSO model requires a minimum CT of 70 ms, whereas the existing FDLP and ILSP models need a maximum CT of 3100 and 3132 ms, respectively. On the other side, under the maximum package count of 300, it is noted that the HFMPSO model offers a least CT of around 32,000 ms, whereas the existing FLDP and ILSP models have offered a maximum CT of 10^{7} and 10^{6} ms, respectively. The abovementioned detailed results analysis showcased the betterment of the HMFPSO model over the compared methods under diverse aspects. 
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