LLM‑SM Hybrid Strategies: Boosting Decision Optimization and Store Design

Recent advances in large language models (LLMs) have sparked interest in their decision‑making capabilities, yet challenges remain; this article explores classic prediction‑optimization pipelines, introduces emerging LLM‑as‑Predictor/Ranker/Optimizer paradigms, and details practical case studies on delivery‑price optimization and intelligent store‑decoration recommendation using LLM‑SM hybrid systems.

Decision OptimizationHybrid ModelingLLM

0 likes · 30 min read

LLM‑SM Hybrid Strategies: Boosting Decision Optimization and Store Design

DataFunSummit

Sep 24, 2023 · Artificial Intelligence

Decision Optimization Algorithms for Port Terminal Scheduling: Case Study, Challenges, and Solutions

This article presents a comprehensive overview of decision optimization algorithms applied to port terminal equipment coordination, detailing a real-world case study, the iECS architecture, implementation challenges across data, computation, and operations, and discusses future trends and best practices for industry deployment.

AI AlgorithmsDecision OptimizationIndustrial AI

0 likes · 19 min read

Decision Optimization Algorithms for Port Terminal Scheduling: Case Study, Challenges, and Solutions

DataFunTalk

Jul 29, 2023 · Operations

Operations Research and Decision Optimization Sessions at DataFun Summit 2023

The DataFun Summit 2023 Decision Intelligence Forum features leading experts from Tsinghua University, Shanshu Technology, Cainiao Network, and Alibaba Cloud presenting cutting‑edge research and real‑world case studies on operations research, supply‑chain optimization, logistics, energy markets, and decision‑making algorithms.

Decision OptimizationIndustrial ApplicationsLogistics

0 likes · 7 min read

DataFunSummit

Apr 22, 2023 · Artificial Intelligence

Applying Causal Inference to Limited‑Resource Decision‑Making

This article explains the fundamentals of causal inference, illustrates its distinction from correlation modeling, and demonstrates how causal techniques can be applied to limited‑resource decision problems such as knapsack optimization, ride‑hailing subsidies, and flight pricing, while also covering experimental design, popular models, evaluation metrics, and open challenges.

Decision Optimizationcausal inferenceexperimental design

0 likes · 15 min read

Applying Causal Inference to Limited‑Resource Decision‑Making

NetEase Yanxuan Technology Product Team

Apr 10, 2023 · Artificial Intelligence

Intelligent Reach System: Modeling, Decision Making, and Optimization for E‑commerce

The paper presents an intelligent reach system for e‑commerce that automatically selects audience, timing, channel, welfare and creative content using user, content and decision models—including XGBoost churn predictions, NLP‑generated copy, Bayesian CTR estimation and linear‑programming optimization—resulting in a 17.4 % rise in paying users and a 5 % revenue boost over manual methods.

Decision OptimizationIntelligent Reache‑commerce

0 likes · 20 min read

Intelligent Reach System: Modeling, Decision Making, and Optimization for E‑commerce

JD Tech Talk

May 12, 2020 · Artificial Intelligence

Designing, Building, and Evaluating an Action Model for Decision Optimization

This article explains how to design, construct, and evaluate an Action Model that quantifies the impact of business decisions on long‑term profit, covering variable selection, model assumptions, algorithm choices, data challenges, and practical evaluation methods such as offline metrics and A/B testing.

Decision OptimizationPredictive Modelingaction model

0 likes · 11 min read

Designing, Building, and Evaluating an Action Model for Decision Optimization