Original pitch for daysdream

The world is a supermarket of things that are available through information costs. daysdream can mitigate those costs significantly. 

The search costs in practical logistics are usually quite significant.

Search includes getting information about possible alternatives (“the list”), then adding details and verifying statements (especially if information does not come from a dedicated, structured real-time source) and finally sifting through the candidate list to enable action choice. 

Technical: Solver (the optimizer)

A Linear Programming model

LP is widely known for suitability to certain kind of optimization. In Daysdream, LP is used as part of the Solver. 

Linear programming in two stages: space -> optimization 

The linear programming -kind of problems arise when there is essentially a “space” of solutions and some contraints, that shape this space. 

In simple terms, the constraints set the geometry of area painted by points (coordinates), from where you can choose a solution. The way to optimize this space (and thus possibly the solution also) is done by applying either the maximization or minimization function on the variables (coordinates). 

Basics of LP – linear programming

Financial or utility-justification of a solution

Basic sanity optimization: Make your benefit > investment

• So you don’t generally want to do idiot things
• This is of course a subjective issue
• Should be defined in a way that a LP optimizer can also understand
• Define formally, or 
• Via examples

In ordinary financial investment decision, companies look for projects that have certain metrics (values). Projects can be ranked by 

• payback time
• Risks
• Comparative benefit against other feasible investments

In short, how to calculate those 2 above?

• Payback time is simple: division with interest rate (i) accounted for
• Comparing a portfolio of investment (from the feasible ones)

Determining feasibility of investment

• Simple rule: do you have the money?
• Real case: do you have the will, the money, the people and partners?