کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6854890 1437598 2018 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Heuristics for the Bi-Objective Diversity Problem
ترجمه فارسی عنوان
اکتشافات برای مسئله تنوع زیستی بی اهمیت
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
The Max-Sum diversity and the Max-Min diversity are two well-known optimization models to capture the notion of selecting a subset of diverse points from a given set. The resolution of their associated optimization problems provides solutions of different structures, in both cases with desirable characteristics. They have been extensively studied and we can find many metaheuristic methodologies, such as Greedy Randomized Adaptive Search Procedure, Tabu Search, Iterated Greedy, Variable Neighborhood Search, and Genetic algorithms applied to them to obtain high quality solutions. In this paper we solve the bi-objective problem in which both models are simultaneously optimized. No previous effort has been devoted to study the “combined problem” from a multi-objective perspective. In particular, we adapt the mono-objective methodologies applied to this problem to the resolution of the bi-objective problem, obtaining approximations to its efficient front. An empirical comparison discloses the best alternative to tackle this NP-hard problem.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 108, 15 October 2018, Pages 193-205
نویسندگان
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