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2 votes

Best algorithm for scheduling interviews

You can model your problem as ILP and implement it e.g., in Pythons PuLP library and solve it with commercial solvers (e.g., GUROBI or CPLEX) or non-commercial solvers such as COIN-OR. However, you ...
PeterD's user avatar
  • 1,666
1 vote

Efficient Algorithm for Scheduling 140 Predefined 1:1 Meetings with Variable Participant Constraints Over 7 Slots?

You could also use a MIP. Here's an example using JuMP and HiGHS: ...
Oscar Dowson's user avatar
1 vote

Efficient Algorithm for Scheduling 140 Predefined 1:1 Meetings with Variable Participant Constraints Over 7 Slots?

With 1:1 meetings only, this is a classical application of graph coloring. The graph has a node for each person and an edge for each required meeting. The edge colors correspond to time slots, and ...
RobPratt's user avatar
  • 32.7k
1 vote
Accepted

Understanding (1+ ε) approximation when objective is discrete

As requested, this answer is a combination of comments I made. I agree that if a $(1+\epsilon)$ approximate algorithm returns a feasible solution to a problem where the second best feasible solution (...
prubin's user avatar
  • 39.5k
1 vote

Making a batch of related linear problems more efficient

Your idea to tighten lower/upper bounds after solving for the min/max of the corresponding variable is fine. It may or may not provide improvements in speed. Taking a bound off the list of things to ...
prubin's user avatar
  • 39.5k
1 vote

Optimization algorithm for space debris

ACO, genetic algorithms and other metaheuristics can be adapted to constrained problems by adding to the objective function penalties for constraint violations and then treating the problem as ...
prubin's user avatar
  • 39.5k
1 vote
Accepted

How do I check convergence in stochastic Benders?

Let the objective of the master problem (the first-stage problem of stochastic programming) be \begin{align} \text{Minimize}~ cx + \frac{1}{|S|} \sum_{s \in S} \theta_s \end{align} where $\theta_s$ ...
Penghui Guo's user avatar
1 vote

Finding lower bound (maximization problem) in Lagrangian Relaxation with subgradient method

The relaxed constraints will typically be violated, but the rest of the constraints will be satisfied. To get a feasible solution to the original problem, you need to modify the relaxed solution ...
RobPratt's user avatar
  • 32.7k

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