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In Fig. 3, the impact of payment satisfaction constraints is even more obvious than that of consumption way satisfaction constraints.
Distinctly, payment satisfaction constraints have a greater influence on the cost than consumption way satisfaction constraints according to the results in Table 3.
In Fig. 2, the load profiles under various payment satisfaction constraints present a greater difference than that under various consumption way satisfaction constraints.
After the customer satisfaction constraints are considered, the price and load profiles present acceptable variation.
This formulation is then extended to include multiple time periods, the potential for product storage, and customer satisfaction constraints on multiple products.
To make the model solvable, a proximate decoupling technique is used to dispose the concave constraint introduced by the customer satisfaction constraints.
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Moreover, compared to the consumption way satisfaction constraint, the payment satisfaction constraint has a heavier influence on the cost.
In the single period case with one customer satisfaction constraint, the nonlinear programming formulation can be solved efficiently using the general purpose nonlinear optimization package, Ipopt.
This chapter focuses on the emergence of constraint satisfaction, with constraint languages, as a new paradigm within artificial intelligence and computer science.
Examples of compositions of sentence cards and their satisfaction of constraints are presented in Table 1.
To verify the satisfaction of constraints efficient algorithms have been developed and implemented.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com