<p>Choosing the best method for decision making is completely related to the assumptions exist in your problem.</p>

<p>The first thing you should consider is that "Are these two parameters completely independent or not?". If we assume transportation time and communication cost are independent, then there is a simple trade-off between them. <a href="https://arxiv.org/pdf/1610.04513.pdf" rel="nofollow noreferrer">On communication cost vs. load balancing in Content Delivery Networks</a> is a published paper which investigated around this trade-off in a CDN.</p>

<p>I suggest you read the three basic methods proposed in this paper. These methods are general enough to use in any independent trade-off problem. So I think it would be enough to get the basic idea.</p>

<hr>

<p><strong>Added Information:</strong></p>

<p>In case of having problem accessing the paper.</p>

<p>The first step to compare cost and time would be scaling these two variables, so it would possible to compare them easily.
<a href="https://en.wikipedia.org/wiki/Normalization_(statistics)" rel="nofollow noreferrer">Wikipedia</a> has a good article on this part. <a href="https://en.wikipedia.org/wiki/Feature_scaling" rel="nofollow noreferrer">Feature scaling</a> would be a good solution for you.</p>

<p>One of the simplest methods for decision making in your problem is calculating the following parameter for each possible solution: </p>

<pre><code>wi = α*ci + (1-α)*ti
</code></pre>

<p>Which <code>ci</code> denotes the scaled cost of picking <code>i</code>th solution and <code>ti</code> denotes the scaled time of choosing <code>i</code>th solution.  The solution with minimum amount of  <code>wi</code> would be the best answer.</p>

<p>In this algorithm <code>0&lt; α &lt;1</code> determines the importance of time and cost. if <code>α=1</code> you are deciding only based on cost and if <code>α=0</code>, time is the only important parameter for you.</p>
Convert time and cost into single uniform measure (or score)
<p>I am developing a simulation model to compare different delivery route options. A critical criteria for selecting the delivery route is to evaluate both the transportation time and cost, and the best achieved balance between time and cost will be selected (or according to certain weight assigned to time and cost). The question is time and cost are different measures and there needs a way to transform the two isolated measures into a single uniform measure. What are the usual methods/algorithms to do this work?</p>