Multi-Criteria Optimal Planning for Energy Policies in CLP
In the policy making process a number of disparate and diverse issues such as economic development, environmental aspects, as well as the social acceptance of the policy, need to be considered. A single person might not have all the required expertises, and decision support systems featuring optimization components can help to assess policies. Leveraging on previous work on Strategic Environmental Assessment, we developed a fully-fledged system that is able to provide optimal plans with respect to a given objective, to perform multi-objective optimization and provide sets of Pareto optimal plans, and to visually compare them. Each plan is environmentally assessed and its footprint is evaluated. The heart of the system is an application developed in a popular Constraint Logic Programming system on the Reals sort. It has been equipped with a web service module that can be queried through standard interfaces, and an intuitive graphic user interface.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A stakeholder-oriented multi-criteria optimization model for decentral multi-energy systems
The decarbonization of municipal and district energy systems requires economic and ecologic efficient transformation strategies in a wide spectrum of technical options. Especially under the consideration of multi-energy …
Stochastic Optimal Control of HVAC system for Energy-efficient Buildings
This paper aims to develop an agile, adaptive and energy-efficient method for HVAC control via Markov decision process (MDP). Our main contributions are outlined First, we formulate the problem as a MDP, which incorporat…
Optimization-based motion primitive automata for autonomous driving
Trajectory planning for autonomous cars can be addressed by primitive-based methods, which encode nonlinear dynamical system behavior into automata. In this paper, we focus on optimal trajectory planning. Since, typicall…
Autonomous DrivingMultiobjective OptimizationTrajectory PlanningIdentifying Best Practice Melting Patterns in Induction Furnaces: A Data-Driven Approach Using Time Series KMeans Clustering and Multi-Criteria Decision Making
Improving energy efficiency in industrial production processes is crucial for competitiveness, and compliance with climate policies. This paper introduces a data-driven approach to identify optimal melting patterns in in…
Decision MakingTime SeriesLow-regret Strategies for Energy Systems Planning in a Highly Uncertain Future
Large uncertainties in the energy transition urge decision-makers to develop low-regret strategies, i.e., strategies that perform well regardless of how the future unfolds. To address this challenge, we introduce a decis…
Decision Making