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Model Perspective
Model Perspective
Nov 21, 2025 · Fundamentals

How to Use Mathematical Modeling to Optimize Everyday Decisions

This article demonstrates how to apply mathematical modeling techniques—such as knapsack optimization, cost‑benefit analysis, graph shortest‑path algorithms, linear programming for nutrition, portfolio theory, and multi‑criteria decision methods—to improve daily time management, shopping, commuting, health, finance, and overall life choices.

AHPLinear ProgrammingPortfolio Theory
0 likes · 10 min read
How to Use Mathematical Modeling to Optimize Everyday Decisions
JD Tech Talk
JD Tech Talk
Apr 30, 2025 · Artificial Intelligence

Adaptive Degradation and Recovery for JD Alliance Recommendation System under High‑Frequency Traffic Spikes

The article presents a comprehensive adaptive degradation and automatic recovery framework for JD Alliance's recommendation system, designed to handle high‑frequency, instantaneous traffic surges during large promotions by combining real‑time monitoring, Wilson‑interval‑based timeout correction, scenario‑aware control, traffic slicing, linear‑programming‑driven chain optimization, and low‑cost business‑agnostic APIs, achieving over 90% reduction in traffic loss and zero incidents.

JD.comLinear Programmingadaptive degradation
0 likes · 11 min read
Adaptive Degradation and Recovery for JD Alliance Recommendation System under High‑Frequency Traffic Spikes
JD Cloud Developers
JD Cloud Developers
Apr 30, 2025 · Artificial Intelligence

How to Keep Recommendation Systems Stable During Sudden Traffic Surges

This article examines the challenges of handling high‑frequency, instantaneous traffic spikes in JD Alliance's recommendation system during major sales events and presents an adaptive, automated degradation and recovery framework that minimizes recommendation loss while maintaining system stability.

Linear Programmingadaptive degradationreal-time monitoring
0 likes · 11 min read
How to Keep Recommendation Systems Stable During Sudden Traffic Surges
ByteDance SYS Tech
ByteDance SYS Tech
Feb 18, 2025 · Operations

How Can Data Center Planning Cut Costs and Boost Efficiency?

This article explains how a mixed‑integer programming tool developed by ByteDance's SYS‑DCD team integrates cost, reliability, delivery speed, and environmental metrics to optimize data‑center planning, reduce power waste, and accelerate deployment across multiple regional scenarios.

Data centerLinear ProgrammingOperations
0 likes · 15 min read
How Can Data Center Planning Cut Costs and Boost Efficiency?
JD Retail Technology
JD Retail Technology
Aug 14, 2024 · Artificial Intelligence

Adaptive Degradation and Recovery for JD Alliance Recommendation System During High‑Volume Promotions

This article describes how JD Alliance built an adaptive degradation and automatic recovery framework for its recommendation system to handle sudden, large‑scale traffic spikes during major sales events, ensuring stability while minimizing recommendation loss through real‑time monitoring, scenario‑aware control, and linear‑programming‑based pipeline orchestration.

JD.comLinear Programmingadaptive degradation
0 likes · 9 min read
Adaptive Degradation and Recovery for JD Alliance Recommendation System During High‑Volume Promotions
Model Perspective
Model Perspective
Feb 1, 2024 · Operations

A Curated Guide to Evaluation and Optimization Models for Researchers

This article compiles a comprehensive list of evaluation and optimization model resources, covering Data Envelopment Analysis, ANP, VIKOR, grey relational analysis, linear and integer programming, and various meta‑heuristic algorithms with example implementations, providing a handy reference for scholars and practitioners.

Linear ProgrammingMetaheuristicsOperations Research
0 likes · 4 min read
A Curated Guide to Evaluation and Optimization Models for Researchers
Model Perspective
Model Perspective
Feb 1, 2024 · Operations

Essential Guide to Evaluation and Optimization Models: Concepts, Methods, and Algorithms

This article compiles recent resources on evaluation and optimization models, covering fundamental concepts, data preprocessing techniques, weighting methods such as TOPSIS and entropy, as well as linear and integer programming, graph theory, network algorithms, and meta‑heuristic approaches like simulated annealing and genetic algorithms.

Linear ProgrammingOperations Researchevaluation models
0 likes · 3 min read
Essential Guide to Evaluation and Optimization Models: Concepts, Methods, and Algorithms
Alibaba Cloud Developer
Alibaba Cloud Developer
Nov 24, 2023 · Operations

What Is an Optimization Solver? A Beginner’s Guide to Solving Real‑World Problems

This article explains what an optimization solver is, defines key terminology, walks through simple equation‑based examples like the chicken‑rabbit problem, expands to real‑world scenarios such as ad allocation and employee benefits, and outlines common solution methods and how to choose appropriate solvers.

Linear ProgrammingModelingOperations Research
0 likes · 17 min read
What Is an Optimization Solver? A Beginner’s Guide to Solving Real‑World Problems
Model Perspective
Model Perspective
Oct 25, 2023 · Operations

How Math Models Can Turn Your Coffee Shop into a Profit Machine

This article shows how forecasting, linear programming, EOQ inventory, pricing elasticity, and location‑selection models can be applied to a coffee shop to predict foot traffic, optimize menus, reduce waste, set optimal prices, and choose the best site, ultimately boosting profitability.

Demand ForecastingLinear ProgrammingPricing strategy
0 likes · 11 min read
How Math Models Can Turn Your Coffee Shop into a Profit Machine
Model Perspective
Model Perspective
Mar 23, 2023 · Fundamentals

Mastering Shortest Path Algorithms: Theory, Models, and Python NetworkX Example

This article explains the shortest path problem in graph theory, presents its integer linear programming model, reviews classic algorithms such as Dijkstra, Bellman‑Ford, and Floyd‑Warshall, and demonstrates solving a city‑flight cost example using Python’s NetworkX library with code snippets.

DijkstraLinear Programminggraph algorithms
0 likes · 7 min read
Mastering Shortest Path Algorithms: Theory, Models, and Python NetworkX Example
Model Perspective
Model Perspective
Mar 6, 2023 · Operations

Master Linear Programming: Theory, Methods, and Python Implementation

Linear programming optimizes a linear objective under linear constraints, and this article explains its theory, common solution methods such as Simplex, Interior‑Point, and Branch‑and‑Bound, illustrates a production‑planning case, and provides a complete Python implementation using SciPy’s linprog function.

Linear ProgrammingPythonbranch-and-bound
0 likes · 7 min read
Master Linear Programming: Theory, Methods, and Python Implementation
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Feb 2, 2023 · Operations

Optimizing Xiaohongshu Splash Screen Ads: Flow Selection and Dynamic Decision Mechanisms

Xiaohongshu’s new “traffic‑optimal + dynamic decision” framework models splash‑screen ad allocation as a linear‑programming problem with volume guarantees, continuously adjusts weights via feedback, and pre‑computes cached decisions to preserve fast app startup, thereby boosting click‑through rates while meeting delivery commitments.

CTR improvementLinear ProgrammingSplash Screen
0 likes · 14 min read
Optimizing Xiaohongshu Splash Screen Ads: Flow Selection and Dynamic Decision Mechanisms
Model Perspective
Model Perspective
Jan 2, 2023 · Operations

How to Linearize Non‑Linear Optimization Problems: Practical Techniques

This article presents a collection of practical techniques for transforming seemingly non‑linear optimization models—such as those with max/min operators, absolute values, fractional objectives, binary products, and special constraints—into equivalent linear programming formulations, enabling the use of mature LP solvers.

Linear ProgrammingOperations Researchmodel linearization
0 likes · 6 min read
How to Linearize Non‑Linear Optimization Problems: Practical Techniques
Model Perspective
Model Perspective
Nov 6, 2022 · Operations

Master Evaluation & Optimization Models: Concepts, Methods, and Algorithms

This curated guide compiles recent articles on evaluation and optimization models, covering concepts, preprocessing techniques, weighting methods such as TOPSIS and entropy, as well as linear/integer programming, graph theory, shortest‑path, max‑flow, simulated annealing, and genetic algorithms.

Linear ProgrammingOperations Researchevaluation models
0 likes · 6 min read
Master Evaluation & Optimization Models: Concepts, Methods, and Algorithms
DeWu Technology
DeWu Technology
Oct 26, 2022 · Operations

Optimization of Packaging Box Design Using Linear and Genetic Algorithms

By formulating the Aurora Blue box design as an integer programming problem and applying both exact linear methods and a tailored genetic algorithm, the study identified an eight‑to‑fifteen‑type solution that raises packing efficiency by 5.49%, cuts paper use 7.6% and trims shipping cost by 0.06 CNY.

Linear Programminggenetic algorithminteger programming
0 likes · 13 min read
Optimization of Packaging Box Design Using Linear and Genetic Algorithms
Model Perspective
Model Perspective
Oct 3, 2022 · Operations

How to Optimize Workforce Planning Over Three Years with Hiring, Training, and Layoffs

This article presents a three‑year workforce planning model that balances hiring, retraining, part‑time staffing, and layoffs while minimizing costs and attrition, using detailed demand forecasts, attrition rates, and constraints to guide optimal decisions for unskilled, semi‑skilled, and skilled workers.

Cost OptimizationLinear Programminghuman resources
0 likes · 8 min read
How to Optimize Workforce Planning Over Three Years with Hiring, Training, and Layoffs
Model Perspective
Model Perspective
Oct 1, 2022 · Operations

How Variable Returns to Scale DEA Reveals Input/Output Slack in a Two‑Stage Model

This article explains how variable‑returns‑to‑scale input‑oriented and output‑oriented DEA models use input and output slacks, introduces a two‑stage linear programming approach to identify non‑zero slacks, and defines full and weak efficiency through formal DEA definitions and illustrative decision‑unit examples.

DEALinear Programmingefficiency
0 likes · 6 min read
How Variable Returns to Scale DEA Reveals Input/Output Slack in a Two‑Stage Model
Model Perspective
Model Perspective
Sep 29, 2022 · Operations

How to Optimize Monthly Oil Purchases and Production for Maximum Profit

Given spot and futures prices for vegetable and non‑vegetable oils, refining capacity limits, storage constraints, and a required product hardness range, this model determines the optimal monthly buying, refining, and inventory decisions that maximize profit for a food‑oil manufacturer over a six‑month horizon.

Linear Programmingoil blendingproduction planning
0 likes · 6 min read
How to Optimize Monthly Oil Purchases and Production for Maximum Profit
Zhuanzhuan Tech
Zhuanzhuan Tech
Sep 8, 2022 · Artificial Intelligence

OCPC Advertising Bidding Strategy: Problem Modeling, Linear Programming Solution, and PID Control

This article presents a comprehensive study of the OCPC advertising bidding product, detailing its business logic, system architecture, linear programming formulation, solution methods using GLPK and Gurobi, parameter analysis, PID feedback control, and both offline and online deployment processes.

AdvertisingLinear ProgrammingOCPC
0 likes · 11 min read
OCPC Advertising Bidding Strategy: Problem Modeling, Linear Programming Solution, and PID Control
Tencent Advertising Technology
Tencent Advertising Technology
Aug 16, 2022 · Artificial Intelligence

CONFLUX: A Request-level Fusion Framework for Impression Allocation via Cascade Distillation

The paper presents CONFLUX, a request-level fusion ranking framework that uses linear programming and cascade distillation to allocate ad impressions between contract and real-time bidding ads, improving platform revenue and ad effectiveness while addressing offline training, latency, and model drift challenges.

CONFLUXKDD 2022Linear Programming
0 likes · 14 min read
CONFLUX: A Request-level Fusion Framework for Impression Allocation via Cascade Distillation
Model Perspective
Model Perspective
Jul 2, 2022 · Operations

Top Resources for Evaluation & Optimization Models – A Curated Guide

This article compiles and categorizes recent model‑related publications, offering a comprehensive list of evaluation‑model resources—including concepts, preprocessing techniques, weighting methods, and various algorithms—and optimization‑model references covering linear and integer programming, graph theory, network flows, and meta‑heuristics.

Linear ProgrammingModelingOperations
0 likes · 4 min read
Top Resources for Evaluation & Optimization Models – A Curated Guide
Model Perspective
Model Perspective
Jun 25, 2022 · Operations

Solving the Transshipment Problem with Python PuLP: A Step-by-Step Guide

This article explains the transshipment problem—a special case of transportation with intermediate warehouses—provides its mathematical formulation, defines indices, decision variables, parameters, objective function and constraints, and demonstrates a complete Python implementation using the PuLP library, including sample data and solution output.

Linear ProgrammingPuLPPython
0 likes · 8 min read
Solving the Transshipment Problem with Python PuLP: A Step-by-Step Guide
Model Perspective
Model Perspective
Jun 23, 2022 · Operations

How Sensitivity Analysis Uncovers Shadow Prices and Slack in Linear Programming

This article explains the fundamentals of sensitivity analysis in linear programming, detailing how changes to objective coefficients, constraint bounds, and coefficients affect model outcomes, and demonstrates computing shadow prices and slack variables using Python's PuLP library with a glass manufacturing example.

Linear ProgrammingPuLPoptimization
0 likes · 6 min read
How Sensitivity Analysis Uncovers Shadow Prices and Slack in Linear Programming
Model Perspective
Model Perspective
Jun 14, 2022 · Operations

Optimizing Relay Team Selection with PuLP: A Step‑by‑Step Guide

Learn how to model and solve a relay‑team selection problem using Python’s PuLP library, defining decision variables, parameters, objective function, and constraints, then executing the solver to obtain the optimal swimmer‑stroke assignments and total time.

Linear ProgrammingPuLPPython
0 likes · 11 min read
Optimizing Relay Team Selection with PuLP: A Step‑by‑Step Guide
Model Perspective
Model Perspective
May 24, 2022 · Operations

Mastering the Minimum Cost Flow Problem: Concepts and Solution Algorithms

This article explains the minimum cost flow problem—delivering a specified amount of flow from supply nodes to demand nodes at the lowest possible cost—covers its linear programming formulation, highlights key solution methods such as successive shortest path, cycle canceling, primal‑dual, network simplex, and outlines its primary applications in distribution network optimization.

Linear ProgrammingOperations Researchalgorithm
0 likes · 3 min read
Mastering the Minimum Cost Flow Problem: Concepts and Solution Algorithms
Model Perspective
Model Perspective
May 3, 2022 · Operations

Master Linear Programming: From Basics to Graphical Solutions

Linear programming, a key optimization technique, is introduced with its core concepts, components, a chocolate production example, standard formulation, and graphical solution method, illustrating how to model real-world resource allocation problems and find profit‑maximizing decisions.

Linear ProgrammingOperations Researchgraphical method
0 likes · 7 min read
Master Linear Programming: From Basics to Graphical Solutions
Efficient Ops
Efficient Ops
Aug 29, 2018 · Big Data

How DataOps and Linear Programming Optimize MaxCompute Capacity Management

This article explains how Alibaba's MaxCompute platform tackles capacity bottlenecks by combining data‑driven insights, linear programming, and automated project migration strategies to predict resource needs, optimize cluster allocation, and quantify migration impacts for improved operational efficiency.

DataOpsLinear ProgrammingMaxCompute
0 likes · 13 min read
How DataOps and Linear Programming Optimize MaxCompute Capacity Management