Multiobjective optimization: When objectives exhibit non-uniform latencies
نویسندگان
چکیده
منابع مشابه
Multiobjective optimization: When objectives exhibit non-uniform latencies
Building on recent work by the authors, we consider the problem of performing multiobjective optimization when the objective functions of a problem have differing evaluation times (or latencies). This has general relevance to applications since objective functions do vary greatly in their latency, and there is no reason to expect equal latencies for the objectives in a single problem. To deal w...
متن کاملSmoothing non-uniform communication latencies for OLTP
Transaction processing applications traditionally run on the high-end servers. Up until recently, such servers had uniform core-to-core communication latencies. Now with multisocket multicores, for the first time we have Islands, i.e., groups of cores that communicate very fast with cores that belong to the same group and several times slower with cores from other groups. In current mainstream ...
متن کاملRobust Optimization for Non-Convex Objectives
We consider robust optimization problems, where the goal is to optimize in the worst case over a class of objective functions. We develop a reduction from robust improper optimization to Bayesian optimization: given an oracle that returns αapproximate solutions for distributions over objectives, we compute a distribution over solutions that is α-approximate in the worst case. We show that deran...
متن کاملMultiobjective Optimization
return on his or her investment with a small risk of incurring a loss; an oncologist prescribes radiotherapy to a cancer patient so as to destroy the tumor without causing damage to healthy organs; an airline manager constructs schedules that incur small salary costs and that ensure smooth operation even in the case of disruptions. All three decision makers (DMs) are in a similar situation—they...
متن کاملEffectiveness of Weighted Aggregation of Objectives for Evolutionary Multiobjective Optimization: Methods, Analysis and Applications
Multiobjective optimization using the conventional weighted aggregation of the objectives method is known to have several drawbacks. In this paper, multiobjective optimization using the weighted aggregation method is approached with the help of evolutionary algorithms. It is shown through a number of test functions that a Pareto front can be achieved from one single run of evolutionary optimiza...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: European Journal of Operational Research
سال: 2015
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2014.09.033