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As translating postures to VR navigation is a first step, an optimal solution would be to map walking movements directly with dedicated hardware, if possible.
An optimal solution would be to assign an orientation to the contigs which minimizes the number of conflicting edges.
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However, the true sales are 0, because none of the farmers located in region 2 buys rice seeds, while the farmers of region 1 would only patronize a facility located in A. If the firm considers segment-specific choice probabilities instead (1 for farmers of region 1 and 0 for farmers of region 2), the optimal solution would be facility location A with an expected number of 49 rice seed customers.
Therefore, escaping from local optimum solutions and finding the global optimal solution would be very difficult in a large problem, even with metaheuristic optimization algorithms.
The optimal solution would be to conduct a time series analysis on historical spam data.
The optimal solution would be using the exhaustive search, where the solution is considered optimal from an aspect that the selected co-occurred features achieve the minimum error.
By increasing the perceived service-distance, the optimal solution would be reached earlier in the iteration process, and the covered demand would increase.
The theoretically optimal solution would be to launch the minimal amount of blocks needed to saturate the device and no more.
If there were only one offer and only one means of getting to the customer, the optimal solution would be pretty simple: Start with your best prospects and work your way down the list until you have exhausted your marketing budget.
The optimal solution would be to record neural signals in animals behaving in their natural environment.
Obtaining practically good solutions, instead of optimal solutions, would be useful for a large dataset because it may not be easy to solve large-scale mixed integer programs on personal computers or workstations.
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CEO of Professional Science Editing for Scientists @ prosciediting.com