Linear Programming

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 ProgrammingReal-time Monitoring

0 likes · 11 min read

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

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.

Linear ProgrammingOptimizationdata center

0 likes · 15 min read

How Can Data Center Planning Cut Costs and Boost Efficiency?

Efficient Ops

Nov 9, 2024 · Operations

How to Fairly Split 8 Swiss Rolls? Solving the Allocation Puzzle with Linear Programming

This article treats the popular "8 Swiss rolls" dilemma as an optimization problem, explains how to model it with linear programming, and presents several algorithmic strategies—including equal division, remainder handling, priority‑based rules, and load‑balancing analogies—along with example Python code.

AlgorithmLinear ProgrammingOptimization

0 likes · 6 min read

How to Fairly Split 8 Swiss Rolls? Solving the Allocation Puzzle with Linear Programming

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 ProgrammingReal-time Monitoring

0 likes · 9 min read

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

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 Programmingevaluation modelsgraph algorithms

0 likes · 3 min read

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

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 Programmingevaluation modelsmetaheuristics

0 likes · 4 min read

A Curated Guide to Evaluation and Optimization Models for Researchers

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.

Linear Programmingdemand forecastinginventory management

0 likes · 11 min read

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

Model Perspective

Sep 20, 2023 · Operations

Unlock Efficiency with Data Envelopment Analysis (DEA) in Operations Research

Data Envelopment Analysis (DEA) is a powerful operations‑research technique that evaluates the relative efficiency of decision‑making units with multiple inputs and outputs by automatically assigning optimal weights, offering a comprehensive alternative to traditional ratio methods, and can be applied through linear programming models and Python implementations.

Data Envelopment AnalysisEfficiency EvaluationLinear Programming

0 likes · 12 min read

Unlock Efficiency with Data Envelopment Analysis (DEA) in Operations Research

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 ProgrammingNetworkX

0 likes · 7 min read

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

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 ProgrammingOptimizationPython

0 likes · 7 min read

Master Linear Programming: Theory, Methods, and Python Implementation

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

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 ProgrammingOptimizationmodel linearization

0 likes · 6 min read

How to Linearize Non‑Linear Optimization Problems: Practical Techniques

Model Perspective

Nov 7, 2022 · Operations

Understanding Data Envelopment Analysis (DEA): Principles, Models, and Applications

This article explains the concept of decision‑making units, the theory behind Data Envelopment Analysis, its linear‑programming models—including primal and dual forms—and how DEA evaluates relative efficiency and scale returns across multiple inputs and outputs.

DEAData Envelopment AnalysisLinear Programming

0 likes · 12 min read

Understanding Data Envelopment Analysis (DEA): Principles, Models, and Applications

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 Programmingevaluation modelsgraph theory

0 likes · 6 min read

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

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 ProgrammingOptimizationgenetic algorithm

0 likes · 13 min read

Optimization of Packaging Box Design Using Linear and Genetic Algorithms

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.

Linear Programmingcost optimizationhuman resources

0 likes · 8 min read

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

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

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 blendingoperations research

0 likes · 6 min read

How to Optimize Monthly Oil Purchases and Production for Maximum Profit

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.

Linear ProgrammingOCPCOptimization

0 likes · 11 min read

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

Model Perspective

Sep 2, 2022 · Operations

Unlocking Efficiency: How Data Envelopment Analysis (DEA) Evaluates Decision‑Making Units

This article explains the theory, models, and dual formulations of Data Envelopment Analysis (DEA), illustrating how it assesses the relative efficiency of decision‑making units using input‑output data, linear programming, and objective weight optimization.

DEAData Envelopment AnalysisEfficiency Evaluation

0 likes · 13 min read

Unlocking Efficiency: How Data Envelopment Analysis (DEA) Evaluates Decision‑Making Units