1.     CHAPTER SIX: CONCLUSION AND RECOMMENDATIONS

Conclusion

Towards the end of this research work, it can now be concluded that the researcher has proficiently documented a research study that is relevant in practical. The discussion on constraints regarding the container loading issues has been categorised through thorough identification. Additionally, the researcher has also competently analyzed how all these related constraints are taken under consideration in the literature sources like articles, peer-reviewed journals that has been published over the last few decades.

Moreover, it can be inferred that significant investigation in terms of container loading field is considerably dealing with paradigm issues has scored the foremost consign, however problems in relevance to the concerned topic have frequently been mistreated in reality. In this research work, stability and orientation constraints has been considered quite often while others like loading priorities and shipment constraints are hardly approached. It has been very clear that container-loading issues in recent times are often featured by the realism that numerous constraints should be dealt with concurrently. In this research work, the literatures addressing this issue have been professedly reviewed.

Amongst the prospectivemodifications, the researcher has identified that only combining container loading as well as automobile routing issues are proficiently scrutinized in a considerable figure of journals. Taking under consideration a bit more the theoretical point of view it can be concluded that the perception of container loading has never been acutely convincing. Modelling approaches applied in a variety of problem types has been in acute scarce so far. Being specific, in regards to the consideration of pertinent constraints in practice, research works are still having the impression of being in its infancy stage. Computational outcomes on a typical data set reflect that the proposed modeling approach could outperform the most well known algorithm in all test data.

In this paper, the strategic adoption of twp-phase actual number encoding strategy has been analysed whereby the design of cargo shipment has been extensively prioritized with the introduction, defining and solving the 3D flexibility container packing issue. The researcher has strategically modelled this container loading issue as a sequence of decision-making problem and afterwards proposed a multi-tasking framework depending on relevant learning outcomes for generation of a packing progression as well as orientations at the same time that can proficiently make use of correlation as well as mitigate disproportion in between the two concerning tasks.

The researcher in due course has also adopted an intra-attention device for addressing of the repeated goods problem appropriately and therefore used the proposal of dynamic mutation operators that has been designed depending on genetic logs for acute prevention of weak convergence, which might outcome from changes in coding algorithm and thereby focused on learning a more reasonable orientation strategy.

Due to presence of huge practical impact, the researcher has strategically focused on the problem of packing cubical shaped goods in an orthogonal fashion considering least surface area in the container. The prevalent heuristic techniques for the classic 3D container loading does not turn out to be well because of this specific NP-hard issue and thereby designing a concerning heuristic specific to the aroused issue has become non-trivial. In this research work, instead of designing heuristics, the researcher has promisingly proposed a novel multitasking outline stringently depending on Selected Learning for apprehending a heuristic like procedure, which is effective in generation of the sequence as well as orientations of goods that are to be packed concurrently. The researcher has analysed numerous comprehensive experiments that are in relevance to real-world transaction order dataset and online tests.

The selected two methods that have been considered in this research work trades off the discrepancy as well as correlation between the tasks and radically outperforms only task Pointer Network as well as multi-task network devoid of selected learning.  The researcher through the implementation of dynamic mutation operator method and two-phase actual number encoding strategy has obtained an average cost reduction compared to the well-designed greedy algorithm that has been previously utilised in mitigating container-loading issue. With the utilization of weak and strong heterogeneous data, the researcher has proficiently analysed these approaches concurrently for testing the effectiveness of proposed methods.

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