How Do You Maximize This Complex Expression With Given Constraints?

  • MHB
  • Thread starter anemone
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    2015
In summary, the main objective of "Maximize Expression with Constraints" is to find the maximum possible value of an expression while satisfying a set of constraints. This problem is typically solved using mathematical techniques such as linear programming. The constraints in this problem can include limitations on resources, physical constraints, or other factors. This problem can be applied to real-world scenarios in various fields. Some benefits of using "Maximize Expression with Constraints" include more efficient and effective solutions, cost savings, improved performance, and the ability to explore different scenarios and trade-offs for decision-making.
  • #1
anemone
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Here is this week's POTW:

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Find the maximum of $a_1+a_2+a_3+a_4-a_1a_2-a_1a_3-a_1a_4-a_2a_3-a_2a_4-a_3a_4+a_1a_2a_3+a_1a_2a_4+a_1a_3a_4+a_2a_3a_4-a_1a_2a_3a_4$

where $|a_i|\le1,\,i=1,\,2,\,3,\,4$.

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  • #2
No one answered last week's problem. :( You can find the proposed solution below:

Let $\small P=a_1+a_2+a_3+a_4-a_1a_2-a_1a_3-a_1a_4-a_2a_3-a_2a_4-a_3a_4+a_1a_2a_3+a_1a_2a_4+a_1a_3a_4+a_2a_3a_4-a_1a_2a_3a_4$

We then see that

$\small \begin{align*}P&=a_1+a_2+a_3+a_4-a_1a_2-a_1a_3-a_1a_4-a_2a_3-a_2a_4-a_3a_4+a_1a_2a_3+a_1a_2a_4+a_1a_3a_4+a_2a_3a_4-a_1a_2a_3a_4\\&=1-(1-a_1)(1-a_2)(1-a_3)(1-a_4)\end{align*}$

given $|a_i|\le1,\,i=1,\,2,\,3,\,4$.It is obvious that $P$ is then less than or equal to $1$.

Therefore, the maximum of $P$ is $1$, occurs at $a_1=a_2=a_3=a_4=1$.
 

FAQ: How Do You Maximize This Complex Expression With Given Constraints?

1. What is the main objective of "Maximize Expression with Constraints"?

The main objective of "Maximize Expression with Constraints" is to find the maximum possible value of an expression while satisfying a set of constraints. This is a common problem in mathematics and engineering, where the goal is to optimize a system or process while adhering to certain limitations or restrictions.

2. How is this problem typically solved?

This problem is typically solved using mathematical techniques such as linear programming, where the constraints and objective function are represented as linear equations and inequalities. These equations are then solved to find the optimal solution that maximizes the expression while satisfying all constraints.

3. What types of constraints can be included in this problem?

The constraints in "Maximize Expression with Constraints" can vary depending on the specific problem at hand. They can include limitations on resources, physical constraints, or other factors that must be considered in the optimization process. Some common examples of constraints include budget limitations, time constraints, and physical space limitations.

4. Can this problem be applied to real-world scenarios?

Yes, "Maximize Expression with Constraints" can be applied to real-world scenarios in a variety of fields such as finance, engineering, and operations research. For example, a company may use this problem to optimize their production process while staying within a given budget, or a transportation company may use it to determine the most efficient routes for their vehicles while adhering to time constraints.

5. What are some benefits of using "Maximize Expression with Constraints"?

Using "Maximize Expression with Constraints" allows for the optimization of a system or process while taking into account various limitations and restrictions. This can lead to more efficient and effective solutions, as well as cost savings and improved performance. Additionally, this problem can also be used to explore different scenarios and trade-offs, providing valuable insights for decision-making.

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