• No results found

Fast Interactive Decision Support for Modifying Stowage Plans Using Binary Decision Diagrams

N/A
N/A
Protected

Academic year: 2020

Share "Fast Interactive Decision Support for Modifying Stowage Plans Using Binary Decision Diagrams"

Copied!
7
0
0

Loading.... (view fulltext now)

Full text

Loading

Figure

Fig. 2.Layout and numbering of bays of a container vessel.
Fig. 3.A BDD of the function f(x1, x2) = x1 ∨x2 using order x1 ≺ x2.High and low edges are drawn with solid and dashed lines, respectively.
Fig. 6.The six valid container configurations of the example shown inFigure 4. The four shaded configurations are represented by the BDD shownin Figure 5 (right) with x2 = 1.
Fig. 7.Screenshot of GUI after start-up (12 containers, 18 cells). Thedarker blue / shaded, the heavier container.
+2

References

Related documents

f FPC005 Estate and Succession Planning f FPC009 Complex Financial Planning Approved for exemptions for CFP 2 – 4 with a 12 subject Masters that includes FPEC study and: f

Only if firms engage in R&D largely (beyond 8.2% R&D intensity) they are perceived as risky investment opportunities by the rating agency, so that such firms are evaluated

These tools are also considerably faster than using SAP Query or standard SAP transactions for a summarized display of single records, especially when you want to display

In Figures 6.6a1 and 6.6a2, we see that our adaptive matrix structures AT Matrix GD and AT Matrix LD outperform all other approaches, followed by the static CSR performance

This chapter discusses parallel communication models and their application to MPI collec- tive algorithms. Section 4.1 provides descriptions of different algorithms for MPI

We first analyze qualitative robustness [in Hampel's (1971) senseJ of these statistics when the initial estimators {T n } (whose distributions we want to approximate

This study shows that nurse in cancer care experience certain aspects of cancer such as psychosocial issues, nutrition, nausea and vomiting and fatigue as problems in their

To that end, we recommend using a linear predictor of your choice (e.g. a linear SVM) and select variables in two alternate ways: (1) with a variable ranking method using a