I have gone through the User manual but still there are lot of functions which I don't know how to use in Optquest. Mainly I am facing problem in defining/selecting variables and using multi objective function in different scenarios. I have completed user manual simple practice model.
Is there more models for optquest available? Is there any study material/case studies available for better understanding of using optquest in different scenarios.
Thank You
@Ramesh Yadav Like Sam mentioned, if you have a model or something specific you want to optimize it would be simple for us to come up with an example for you. For example, what variables do you want to set, what objectives do you have, etc. Or are you just wanting another general example?
@Sam Stubbs @Adrian Haws Firstly, Thank You.
Actually I want to optimize automated warehouse, it consists of racks for inventory storage. 8 AGV's and 1 picking station.
Orders are coming and AGVs are working for fullfilment of that order. At picking station all the items needed for order completion are combine and then only it can be dispatched.
I want to know impact of increasing picking station on AGV's utilisation rate or distance travel by AGV's. I can also keep minimization of order fulfillment rate as one of the objectives.
Please give me your valuable suggestions.
If you are already looking at seeing what the impact of increasing the picking station, that might be something you'd better discover using the experimenter and examining the different variables and scenarios in that situation. However, maybe Adrian or someone else on the forum with more experience in OptQuest could better direct you in this case.
Unfortunately we don't have any additional training materials at this time. But perhaps you could expound more on what specifically you're trying to implement, and maybe we could provide some insight there.
Optquest varies continuous values. Such values are mostly units of time, length or current. Optquest can varies in discrete steps, too. That is a feature which does the Experimenter already. In a model where the optimum lays in the amount of used objects, the amount is translated in or is controlled by discrete values. A table is an instrument of use. The row of a table defines the objects that are stopped on reset or on simulation run start of the model. Optquest chooses on each variation step one row of the table. Therefore each row contains all objects to activate or deactivate. Or a loop activates the objects from row number one to the actual highest row number that Optquest varies.
Other possible discrete values are the amount of output-, input- or center ports to use in combination of a round robin fashion or random fashion. The highest port number is set by a label value. Then this value is varied by Optquest.
Lists are an instrument, too. If you query a list you can add an list item which contains the number of the variation step. In Optquest you pull from the list where the varied number is lower and equal to the list attribute.
@Jorg Vogel Thank You. It will help me in further problems.
@Sam Stubbs I will try using experimenter. Thank You.
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