SCIP Mixed Integer Quadratic Programming using - scip

I want to use SCIP included in my source code (C++) to solve a MIQP and did not find how to do it besides this FAQ entry:
Nonlinear objective functions are not supported by SCIP and must be modeled as constraint function. Note, that the support for non-quadratic nonlinear constraints is still in a BETA-stadium and not yet as robust as the rest of SCIP. Missing bounds on nonlinear variables and tiny or huge coefficients can easily lead to numerical problems, which can be avoided by careful modeling.
I already managed to construct the expression tree for the objective function. I would like to know:
If MIQP's must me modeled as MINLP's, then how does this constraint function modelling work? Is the upper bound changeable?
If there are specific methods for MIQP's, where can I found documentation about it?

Have a look at the examples at
http://scip.zib.de/doc/examples/CallableLibrary/
If you just want quadratic, then you can create quadratic constraints directly in SCIP using the constraint handler for quadratic constraints:
http://scip.zib.de/doc/html/cons__quadratic_8h.php
For the methods used by SCIP to handle the quadratic parts of an MIQP, see
http://nbn-resolving.de/urn:nbn:de:0297-zib-59377 and the references therein.

Related

Pyomo.dae custom finite difference scheme

I am new to Pyomo and would like to implement a custom finite difference discretization scheme. Pyomo documentation implies one needs to copy a function for the forward difference method and just replace the equation next to the first return statement with a new one. After implementing a custom finite difference method using the above function template, the only other change that must be made is to add the custom method to the all_schemes dictionary in the dae.finite_difference class.
Can anyone please provide an example of solving an optimal control problem with manual implementation of finite difference (NOT collocation) discretization?

Is there a useful "number-like" generic constraint in Kotlin?

I'm writing a matrix and a vector class, and I'd like to make it usable with all "sensible" numerical data types, not only for the BigFraction data type I wrote myself for my current purpose.
Therefore, I'm wondering whether there is an interface which requires + and * to be implemented (or perhaps even more operator functions).
Thus, I'd like to have a useful generic constraint.
Thanks a lot in advance!

Call-by-need and call-by-name reduction relation semantics

While trying to summarize my knowledge about lambda calculus, I understood that I'm quite familiar with call-by-value but I've never seen сall-by-need reduction semantics. I know the definition, but it would be great to see precise meaning.
This is what I have for call-by-need and call-by-value (not very detailed description):
Call-by-value
Small Step
Values
β-reduction
Evaluation context
Big Step (with closures and environment)
Closures
Environment
Reduction
Call-by-name
Small Step
β-reduction
Evaluation context
I guess there is also a big step, which must be quite similar to call-by-value, but once again, its better to see it once.
So I will be grateful if someone can extend my list with call-by-need.
Currently I cannot write this in Tex, but the main thing is: when using pure functions the evaluated value of a function with the same parameter(s) will be always the same, so while you are in the same body, you can use the evaluated reference instead of evaluating it again.
For more information see:
http://repository.readscheme.org/ftp/papers/plsemantics/felleisen/jfp96-af.pdf

Should I use OOP when encapsulation is essentially ignored?

I am making a Mathematics web program which allows the user to compute and prove various quantities or statements, e.g. determinant of a matrix, intersection of sets, determine whether a given map is a homomorphism. I decided to write the code using the OOP paradigm (in PHP, to handle some of the super heavy computations that a user's browser might not appreciate), since I could easily declare sets as Set objects, matrices as Matrix objects, etc. and keep some of the messy details of determining things such as cardinality, determinants, etc. in the background. However, after getting knee-deep in code, I'm wondering if deciding on OOP was a mistake. Here's why.
I'll use my Matrix class as a simple example. Matrix has the following attributes:
name (type String) (stores name of this matrix)
size (type array) (stores # rows and # columns of this matrix)
entries (type array) (stores this matrix's entries)
is_invertible (type Boolean) (stores whether this matrix can be inverted)
determinant (type Int) (stores the determinant of this matrix)
transpose (type array) (stores the transpose of this matrix)
Creating a new matrix called A would be done like so:
$A = new Matrix("A");
Now, in a general math problem concerning matrices, it could be that we know the matrix's name, size, entries, whether it's invertible, its determinant, or its transpose, or any combination of the above. This means that all of these properties need to be accessible, and certainly any of these properties can be changed by the user, depending on what's given in the problem. (I can give examples of problems for any of these cases, if needed.)
The issue I'm having, then, is that this would break the encapsulation "rule" of OOP ("rule" in quotes since, from what I understand, it's not a hard-and-fast rule, just one that should be upheld to the greatest extent possible). I did some searching on when getters and setters should be used, or even IF they should be used (seems odd to me that they wouldn't, in an OOP setting...), but this did not seem to help me much, as I found many contradictory answers and case-specific opinions.
So, my overall questions are: when the user needs access to modify many (if not all) of an object's attributes, but a class-oriented design seems to be ideal for addressing the programming problem,
Is OOP the best way to structure the code, despite essentially ignoring encapsulation altogether?
Is there an alternative to OOP which allows high user access while maintaining the OO "flavor" (i.e. keeping sets, matrices, etc. as objects)
Is it ok to break the encapsulation rule altogether once in a while, if the problem calls for it? Or is that not in the spirit of OOP?
What you are trying to do is not necessarily outside the scope of OOP. The thing is that you have a different model than what would usually be described in programming textbooks (where, for example, the values of the matrix would be always present and all of the functions could be simple methods). (Perhaps this is why the question was unfairly downvoted.) Nothing prevents you from storing values like "is_invertible" internally and implementing setter and getter methods. Doing this might make sense if you are trying to learn OOP. But I think other problems (see coding textbooks) might be easier for learning purposes. I see that a remote goal would be to capture some of mathematics as an OOP framework. But the whole mathematical universe is immensely richer than any fixed architecture (results like Gödel's theorem put a theoretical limit). You can only succeed in developing a framework for a very narrow application, for example solving certain equations. That's what symbolic algebra programs do: you can look at how, for example, SymPy or perhaps parts of Maple and Mathematica are implemented. In my view, the OOP paradigm can be both very useful and too restrictive / unnecessary depending on the task (you can certainly find more about shorcomings of OOP in Wikipedia or elsewhere). Also, your problem can be seen as writing a small programming language - in many of them you have sets, numbers, etc as objects.
You can use only rudimentary OOP or no OOP at all. You can use functional programming.
You should Google/read more about this on this or other sites. Is it OK to sometimes walk across the road when the red traffic light is on?

Difference between OOP and Functional Programming (scheme) [closed]

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Closed 11 years ago.
I'm watching a video course/lectures from Stanford. The course is "The Structure and Interpretation of Computer Programs"
In the first OOP lecture, the instructor (Brian Harvey) describes an OOP method as one that gives different answers for the same question, while a function in functional programming gives a certain output for a certain input.
The following code is an example of a method in OOP that gives a different answer each time it's called:-
(define-class (counter)
instance-vars (count 0))
(method (next)
(set! count (+ count 1))
count) )
Now although the course is illustrated by scheme, I didn't pay much attention to the language itself, and so I can't explain the code; but can't a similar function "next" do the same thing as this "next" function?
In C, I would declare a global variable, and each time increase it by one when calling next. I know C is procedural, but I'm guessing a similar thing can be done in Scheme.
Well. With all due respect to the lecturer, these are slightly fishy definitions of both "OOP" and "functional programming". Both terms are consistently used, well, inconsistently, both in industry and academic contexts, not to mention informal use. If you dig a bit deeper, what's really going on is that there are several orthogonal concepts--different axes along which a choice is made in how to approach a program--that are being conflated, with one set of choices being arbitrarily called "OOP" despite not having anything else tying them together.
Probably the two biggest distinctions involved here are:
Identity vs. value: Do you model things by implicit identity (based on memory location or whatnot) and allow them to change arbitrarily? Or do you model things by their value, with no inherent notion of identity? If you say x = 4 does that mean that x is an alias to the timeless Platonic ideal of the number 4, or is x the name of a thing that's currently a four, but could be something else later (while still being x)?
Data vs. behavior: Do you work with simple data structures whose representation can be inspected, manipulated, and transformed? Or do you work with abstracted behaviors that do things, representing data only in terms of the things you can do with it, and let these behavioral abstractions operate on each other?
Most standard imperative languages lean toward using identity and data--pointers to C structs are about as purely this approach as possible. OOP languages tend to be defined largely by opting for behavior over data, often leaning toward identity as well but not consistently (cf. the popularity of "immutable" objects).
Functional programming usually leans more toward values rather than identity, while mixing data and behavior to various degrees.
There's a lot more going on here as well but I think that's the key part of what you're wondering here.
If anyone's curious I've elaborated a bit on some of this before: Analyzing some essential concepts of many OOP languages, more on the identity/value issue and also formal vs. informal approaches, a look at the data/behavior distinction in functional programming, probably others I can't think of. Warning, I'm kind of long-winded, these are not for the faint of heart. :P
There is a page on the excellent Haskell wiki, where differences in Functional Programming and OOP are contrasted. The Haskell wiki is a wonderful resource for everything about functional programming in general in addition to helping with the Haskell language.
Functional programming and OOP Differences
The important difference between pure functional programming and object-oriented programming is:
Object-oriented:
Data:
OOP asks What can I do with the data?
Producer: Class
Consumer: Class method
State:
The methods and objects in OOP have some internal state (method variables and object attributes) and they possibly have side effects affecting the state of computer’s peripherals, the global scope, or the state of an object or method. Variable assignment is one good sign of something having a state.
Functional:
Data:
Functional programming asks How the data is constructed?
Producer: Type Constructor
Consumer: Function
State:
If a pure functional programming ever assigns to a variable, the variable must be considered and handled as immutable. There must not be a state in pure functional programming.
Code with side effects is often separated from the main purely functional body of code
State can be passed around as an argument to a function, this is called a continuation.
Functional substitutes for OOP generators
The way to do something similar to OOP style generators (which have an internal state) with pure functional programming is to approach the problem from a different point of view, by using one of these solutions depending on the use case:
1. Process some or all values in a sequence:
Type of sequence can be list, array, sequence or vector.
Lisp has car and Haskell has first, which take first item from a list.
Haskell also has take, which takes the first n items, and which supports lazy evaluation and thus infinite or cyclic sequences – like OOP generators do.
Both have first, and different map, reduce or fold functions for processing sequences with a function.
Matrices usually also have some ways to map or apply a function to each item.
2. Some values from a function are needed:
The indices might be from a discrete or continuous scale (integers or floats).
Make one pure function to generate the indices (events) and feed those to another pure function (behaviour). This is called Functional reactive programming. This is a form of Dataflow programming along with cell-oriented programming. The Actor model is also somewhat similar in operation, and a very interesting alternative to threads with handling concurrency!
3. Use a closure to confine and encapsulate the state from the outside
This is the closest subsitute to OOP way with generators (which I think actually originated to imitate closures), and also farthest from pure functional programming, because a closure has a state.
"Functional" in functional programming has traditionally referred to the meaning of mathematical functions. That is, the output of a mathematical function is based solely on the inputs passed to it. Nowadays such programming is more often called pure functional programming.
In pure functional programming reassigning state is not allowed, thus writing a function such as your C example would not be possible. You are only allowed to bind a value to a variable once. An example of a language where this would not be possible is Haskell.
Most functional programming languages (Scheme included) are unpure and would allow you to do so. Said that, what the lecturer is telling is that writing such a function is not possible in the traditional sense of functional programming.
Well, yeah, you could do that in C.
But its not the same - in C++ you can make each object have its own count.