Abstract: In scenarios where multiple decision-makers operate within a common decision space, each focusing on their own multi-objective optimization problem (e.g., bargaining games), the problem can ...
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Alibaba's Metis agent cuts redundant AI tool calls from 98% to 2% — and gets more accurate doing it
Alibaba's HDPO framework trains AI agents to skip unnecessary tool calls, cutting redundant invocations from 98% to 2% while ...
Abstract: Expensive multi-objective binary optimization problems frequently emerge in real-world applications, where evaluating a single solution incurs significant computational or physical costs.
In today’s retail world, too much inventory is as risky as carrying too little. One U.S. grocery chain, operating a hub-and-spoke distribution model, held 57 days of supply for dry food. Inventory ...
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ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
In this tutorial, we implement an advanced Optuna workflow that systematically explores pruning, multi-objective optimization, custom callbacks, and rich visualization. Through each snippet, we see ...
This repository contains Evolutionary Algorithms that can be used for multi-objective optimization. Interactive optimization is supported. Methods such as RVEA and NSGA-III can be found here.
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