{"product_id":"new-archive-based-evolutionary-multi-objective-algorithms-von-xavier-esquivel","title":"New Archive Based Evolutionary Multi-Objective Algorithms","description":"\u003cp\u003eIn this work we deal with the design of archive  based multi-objective evolutionary algorithms (MOEAs) for the numerical treatment of multi objective optimization problems (MOPs). In particular, we design two generational operators­ one mutation and one crossover operator that are tailored to a class of archiving strategies and propose a new evolutionary  strategy. Furthermore, we investigate here two widely used indicators for  the evaluation of Multi-objective Evolutionary Algorithms, the Generational Distance (GD) and the Inverted Generational Distance (IGD), with respect to the properties of ametric. We de¿ne a new performance indicator, ¿p, which can be  viewed as an ¿averaged Hausdor¿ distance¿ between the outcome set and the Pareto front and which is composed of (slight modi¿cations of) the well-known indicators Generational Distance (GD) and Inverted Generational Distance (IGD). We will discuss theoretical properties of ¿p (as well as for GD and IGD) such as the metric properties and the compliance  with state-of-the-art multi-objective evolutionary algorithms (MOEAs).\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783659184963\"\u003e\u003ch3\u003eEvolutionary Computation\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Softcover - 9783659184963","offer_id":39489912832093,"sku":"9783659184963","price":59.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/327f2e7a-d5fb-46ad-9351-9f3d185b9a7a.jpg?v=1773122231","url":"https:\/\/shop.autorenwelt.de\/products\/new-archive-based-evolutionary-multi-objective-algorithms-von-xavier-esquivel","provider":"Autorenwelt Shop","version":"1.0","type":"link"}