The hierarchical multi-objective policy optimization is a policy-centric multi-level bottom-up iterative approach, designed from a developing country perspective, utilizing the optimality principle of dynamic programming.
The two main objectives of this paper are: (1) to present an holistically designed ecological-economic model to evaluate farm and field-level environmental-economic tradeoffs with special reference to multi-objective policy-making and (2) to evaluate the impact of the Agenda 2000 reform on sustainability of organic farming.
He is Chair of a Working Group on multi objective optimization.
data-centric multi objective QoS-aware routing protocol.
In this paper, we propose a novel method, called direct policy conditioning (DPC), that combines direct policy search, multi-objective evolutionary algorithms, and input variable selection to design dynamic constraints that change according to the current system conditions.
Subsequently, the paper presents the multi-objective optimization of proof testing policies with genetic algorithms, using this model for quantification of average probability of failure on demand as one of the objectives.
This paper introduces a new development for modelling the time-dependent probability of failure on demand of parallel architectures, and illustrates its application to multi-objective optimization of proof testing policies for safety instrumented systems.
This study presents a novel approach which combines direct policy search and multi-objective evolutionary algorithms to solve high-dimensional state and control space water resources problems involving multiple, conflicting, and non-commensurable objectives.
Karimi-Nasab et al. (2013) proposed a multi-objective approach to determine the distribution policy for a wholesaler.
In this sense, cloud resource management requires complex policies and decisions for multi-objective optimization.
More specifically, we employ Multi-objective Programming (MP) to seek so-called efficient policies.
