optimization

问题 Given N pairs, we have to find the count of pairs that contain an element k in their range, i.e : If a Pair i is defined as (X i ,Y i ), then if Pair i contain K in its range, then X i <= K <= Y i . Now we are given Q such queries to handle with each query consisting of an integer K. Input: The first line contains two space-separated integers N and Q. Next N lines follow where each line denotes a pair. Each line contains two space-separated integers. Next Q lines follow where each line

问题 Say I have a non-convex objective function loss that takes a np.ndarray named X whose shape is (n,) and returns a float number. The objective has many many many local minima, since it's essentially a function of np.round(X * c, 2) where c is another constant array of shape (n,). You can imagine something like this: def loss(X: np.ndarray) -> float: c = np.array([0.1, 0.5, -0.8, 7.0, 0.0]) X_rounded = np.round(X * c, 2) return rosen(X_rounded) The linear constraint is expressed with two

问题 This is a follow-up to an earlier specific question, but as I add more complexity to the problem formulation, I realize that I need to take a step back and consider whether cvxpy is the best tool for my problem. What I'm trying to solve: create the largest cluster of a category and company where the average values are above a particular threshold. The trick is that if we include particular categories for a company in the cluster, in order to add another company, that company also should have

问题 I am writing a virtual machine that has 8 bit opcodes, and one of the common types for the instructions has the 8-bit opcode, followed in memory by a 56 bit signed integer operand. Originally, I was going to implement this instruction as follows: struct machine_op { std::uint64_t opcode:8 std::int64_t operand:56; }; However, Ive heard no end of comments that using bitfields like this would not be portable, and in particular, it would not guarantee that the operand field would actually be in

问题 I have a problem that I don't know how to add indicator constraints in pulp . Can anyone help me? For example: I have a decision variable x[(i,j)] , LpBinary and a continuous variable u[i] When x[(i,j)] equals 1 , then u[i] + q[j] == u[j] ( q is just the demand of customers) Thank you for your helping. 回答1: Welcome to SO! My interpretation of your question is that you have binary variables x[(i,j)] , and continuos variables u[i] . When x[(i,j)]==1 then you want to enforce a constraint as

问题 I have a problem that I don't know how to add indicator constraints in pulp . Can anyone help me? For example: I have a decision variable x[(i,j)] , LpBinary and a continuous variable u[i] When x[(i,j)] equals 1 , then u[i] + q[j] == u[j] ( q is just the demand of customers) Thank you for your helping. 回答1: Welcome to SO! My interpretation of your question is that you have binary variables x[(i,j)] , and continuos variables u[i] . When x[(i,j)]==1 then you want to enforce a constraint as

问题 from typing import List def countTeams(num: int, skills: List[int], minAssociates: int, minLevel: int, maxLevel: int) -> int: # WRITE YOUR BRILLIANT CODE HERE qualified = [] possible_teams = [[]] for a in skills: if minLevel <= a <= maxLevel: qualified.append(a) num_teams = 0 while qualified: person = qualified.pop() new_teams = [] for team in possible_teams: print(team) print(person) new_team = [person] + team print(new_team) if len(new_team) >= minAssociates: num_teams += 1 new_teams.append

问题 the program is a system that shows media: images, videos and keeps alternating between them. the problem is the use of increasing memory: after the programming running for 30 minutes, it consumes 1.2gb of ram I do not have much idea of what I can do, I believe that the reason for the increasing memory consumption would be recursion (the function calls itself) or the fact that every time it gives a picture it creates a thread, and when it video it uses the technically 'correct' which is a

问题 Imagine this piece of code: void Function(int16 *src, int *indices, float *dst, int cnt, float mul) { for (int i=0; i<cnt; i++) dst[i] = float(src[indices[i]]) * mul; }; This really asks for gather intrinsics e.g. _mm_i32gather_epi32. I got great success with these when loading floats, but are there any for 16-bit ints? Another problem here is that I need to transition from 16-bits on the input to 32-bits (float) on the output. 回答1: There is indeed no instruction to gather 16bit integers, but

问题 I'm doing [very] intense numerical calculations related to physics using solvers written in C++. A single run can take up to few hours on my PC, and one need dozens. I've found that it is possible to significantly (2-5x) decrease the time almost without losing accuracy, if one tabulates smooth functions and uses tabulated values instead. The code below illustrates what do I mean: main.h #pragma once #include <iostream> #include <chrono> #include <math.h> #include <memory> typedef double(*fnc)