Questions tagged [linearization]

For questions related to techniques for converting nonlinear expressions in optimization models into equivalent (or approximately equivalent) linear ones.

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Linearize a highly non-linear objective function

[EDIT] : The formula below is updated to remove the radical, 0.5 in the term $(I_{i,v} \cdot \Delta t)$ and constant temperature $T$ replces temperature as function of current. [EDIT] :The values of ...
Jose_Peeterson's user avatar
3 votes
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From Quadratic to MILP?

I am playing around with some Quadratic Programs (QPs), and I want to check if my reasoning is right concerning a re-modeling from QP to MILP. So, let's consider the below QP: (QP) $\min c^T x + x^T Q ...
Matheus Diógenes Andrade's user avatar
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Linearize objective function with non-linear terms

I have a problem with linear constraints but in the objective function I want to have some linear terms along with a $x^2$ term. So it is like the following: $$\min \sum \limits _i \sum \limits _j (a[...
christouandr7's user avatar
3 votes
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Function approximation of a complex objective function

I would like to approximate the following objective function using a simpler function that can use be defined in gurobi. \begin{equation} \min_{I_{i,v}} \ \sum^{N_v}_{v}\sum^{TT_v}_{i} \ C_{loss,...
Jose_Peeterson's user avatar
3 votes
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Linearization of a quadratic model, what is the difference while using gurobi?

I have a quadratic model of parking $N$ cars in $S$ separate lanes as follows. Each car has an arrival time and a departure time. Departure follow the last in first out principle. The objective is to ...
OR Junior's user avatar
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How to linearize a max min objective function?

Let us suppose that I have a $\max \min$ objective function that only depends on one set of variables: $\underset{x}\max \underset{y}\min dy$ Associated with the linear set of constraints and right ...
JKHA's user avatar
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Linearization of the shifted copy of a function

Suppose in a model I have the expression $y_{1}(x) = 10 + 5 x^2$ where $x \in [0,20]$ is a continuous variable. In order to be able to use an MILP solver, I piecewise linearise $z_{1} = x^2$, by ...
Clement's user avatar
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Linearisation using SOS2

I am trying to linearise the following expresssion. $C(k) = B(k) e^{-d(k)}, B(k) \ge 0 , d(k) \ge 0 $ I am trying to do this by using SOS2 sets. I set $X(k) = e^{-d(k)}$ and I get $C(k) = B(k) X(...
Clement's user avatar
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2 votes
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The linearization of the logical constraints

I know the logical constraints can be linearized by either the logical representation of whose relation, (for pure binary variables e.g. CNF/DNF) or for general form by using Big-M formulation. As I ...
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Moment based linearization of PDF for LP based optimization

Suppose I’m interested in modeling risk/volatility using the Cauchy distribution and I’d like to optimize some allocations using linear programming. The Cauchy distribution is quadratic in nature but ...
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transform minimize weighted sum of absolute value into a linear optimization

For example, we have an optimization problem $$ \min \sum_{i=1}^{n} |w_{i} - a_{i}| b_{i} \quad \text{s.t.} \quad \sum_{i=1}^{n} c_i w_i = 0 $$ and $a_i, b_i, c_i$ are given. How to convert it into a ...
Pique's user avatar
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How to linearize a product and ratio of $x$ and $y$ where $x$ is binary and $y$ is a continuous variable?

I am an electrical engineer who is currently learning about optimization. From this post, they have shown how to linearize the product of two binary variables. But in my case, I have a product $x \...
Tuong Nguyen Minh's user avatar
1 vote
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Linearization of Conditional Constraints for MIP using Cplex

I'm currently working on a mixed-integer programming (MIP) problem and I'm trying to implement a set of conditional constraints in CPlex. These constraints involve decision variables that are indexed ...
B.Kim's user avatar
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1 answer
163 views

Nonlinear fractional objective function

Could you please teach me when an optimization model with fractional terms in the objective function can be linearized or solved optimally? I only know that if the objective function has a single ...
Reza Farahani's user avatar
1 vote
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81 views

Converting Nonlinear Program into an LP

I have a problem with a nonlinear objective function which is \begin{align}\min&\quad Z_j\cdot(N_j)^{0.5}\end{align} where $j$ is the index. I want to know how can I turn it into a linear ...
Paradise's user avatar
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Production scheduling

I'm formulating a scheduling problem with the following decision variables: $$X_t \space \text{is power sold to market in time period t} \\ Y_t \space \text{is power used for production in time period ...
fikacoder's user avatar
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Handling Variable Division in CVXPY for Calculating Annualized Rate of Change

I am working with a dataset that contains multiple entries for different IDs across various years. Some IDs might have a gap of years between entries. My goal is to solve an optimization problem using ...
user760900's user avatar
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Transforming a quadratic constraint into a linear constraint

I have a problem with a quadratic constraint and I want to transform it into a linear constraint. This would help to reduce the computational time of my problem. Following constraint should be ...
Adri's user avatar
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Optimize revenue function with log part

I am working on an optimization problem where I aim to maximize revenue. My current model has the following objective function: $$ Sales(P_i) * log(P_i - const_i))$$ where $P_i$ represents the price ...
MarcM's user avatar
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Interpret the formulation of a pricing model in crowdshipping

I am trying to run the pricing model from the paper "Designing pricing and compensation schemes by integrating matching and routing models for crowd-shipping systems" on python with Gurobi, ...
Last_Mile's user avatar
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How to linearize such a constraint?

My original content was like this: Assuming that server $k$ can only allocate corresponding computing functions to MU $i$ after receiving their tasks. Let $$ y_{i,k,t} = \begin{cases} 1 & \text{if ...
Yunqi Li's user avatar
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Resource selection problem with non-linear objective function

I have an optimisation problem to solve but I can't model it correctly. Any insight is welcome :) It has been a few years since my optimisation classes in university, and while I have forgotten a lot ...
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