Top new questions this week:
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There are many (numeric) optimizers which solve some subset of the set of multi-objective, black-or-grey-or-white box, robust, stochastic, mixed-integer, non-linear, non-smooth, manifold-constrained ...
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There are two non-negative integer variables $q$ and $p$, where only one of them can take a positive value. To impose this relation, I write:
\begin{align}
q &\leq M(1 - y) \tag1 \\
p &\leq M(...
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For a given optimization problem there are often many known math programming formulations.
For example for the TSP here is a survey https://link.springer.com/chapter/10.1007/3-540-36626-1_5
of many ...
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I have an LP that has exponentially many constraints, and just linearly many variables. The dual of the problem, therefore, has exponentially many variables, while just linearly many constraints. My ...
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Consider an optimization problem with $n>3$ objectives.
For handling this there exists often two approaches:
a) some weighting of the objectives,
b) fix an order of objectives and then optimize ...
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I am trying to solve a nonlinear problem with only a set of continuous variables (where the nonlinearity stems from negative inconsistent - across differently indexed variables - large powers), e.g., ...
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Suppose that we have a standard TSP, except that it is required to visit each city at least
once instead of exactly once. The challenge is: how to transform this problem to a
standard TSP? To that ...
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Greatest hits from previous weeks:
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In Python's PuLP package, how can I get the value of a decision variable?
For example, if I declare a variable—
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Many abbreviations are used in Operations Research. For example, we have abbreviations for problem classes (LP, MIP), solution methods (IPM), and specific problems (TSP, VRP).
Which abbreviations are ...
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So I noticed, that a lot of students taking OR-classes come from non-computer science backgrounds (e.g. buissiness administration). They typically had only one other class in their first semester ...
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Is anyone aware of a medicine/vaccine related challenges with a good problem definition and some available input datasets, ideally related to COVID-19? What kind of constraint solving challenges would ...
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I noticed the similarities between KKT and complementary slackness, but I do not fully understand it.
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I'm new to the OR world, and trying to learn the various tools available. I originally thought that Pyomo and Google OR tools were open source alternatives to commercial solvers like Gurobi or CPLEX.
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There is a method of solving a minimization problem using the simplex method where you just need to multiply the objective function by -ve sign and then solve it using the simplex method. All you need ...
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Can you answer these questions?
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I am fairly new to Pyomo and Gurobi. I'd like to find 20 sets of different solutions that meet the following constraints.
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I am solving a MILP model in C++ using Gurobi 10.1.
I retrieve the CPU time of my C++ program under Linux via the following commands:
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