32,655 research outputs found
The energy scheduling problem: Industrial case-study and constraint propagation techniques
This paper deals with production scheduling involving energy constraints, typically electrical energy.
We start by an industrial case-study for which we propose a two-step integer/constraint programming method. From the industrial problem we derive a generic problem,the Energy Scheduling Problem (EnSP). We propose an extension of specific resource constraint propagation techniques to efficiently prune the search space for EnSP solving. We also present a branching scheme to solve the problem via
tree search.Finally,computational results are provided
Global supply chains of high value low volume products
Imperial Users onl
The relevance of outsourcing and leagile strategies in performance optimization of an integrated process planning and scheduling
Over the past few years growing global competition has forced the manufacturing industries to upgrade their old production strategies with the modern day approaches. As a result, recent interest has been developed towards finding an appropriate policy that could enable them to compete with others, and facilitate them to emerge as a market winner. Keeping in mind the abovementioned facts, in this paper the authors have proposed an integrated process planning and scheduling model inheriting the salient features of outsourcing, and leagile principles to compete in the existing market scenario. The paper also proposes a model based on leagile principles, where the integrated planning management has been practiced. In the present work a scheduling problem has been considered and overall minimization of makespan has been aimed. The paper shows the relevance of both the strategies in performance enhancement of the industries, in terms of their reduced makespan. The authors have also proposed a new hybrid Enhanced Swift Converging Simulated Annealing (ESCSA) algorithm, to solve the complex real-time scheduling problems. The proposed algorithm inherits the prominent features of the Genetic Algorithm (GA), Simulated Annealing (SA), and the Fuzzy Logic Controller (FLC). The ESCSA algorithm reduces the makespan significantly in less computational time and number of iterations. The efficacy of the proposed algorithm has been shown by comparing the results with GA, SA, Tabu, and hybrid Tabu-SA optimization methods
Quasi-dynamic Load and Battery Sizing and Scheduling for Stand-Alone Solar System Using Mixed-integer Linear Programming
Considering the intermittency of renewable energy systems, a sizing and
scheduling model is proposed for a finite number of static electric loads. The
model objective is to maximize solar energy utilization with and without
storage. For the application of optimal load size selection, the energy
production of a solar photovoltaic is assumed to be consumed by a finite number
of discrete loads in an off-grid system using mixed-integer linear programming.
Additional constraints are battery charge and discharge limitations and minimum
uptime and downtime for each unit. For a certain solar power profile the model
outputs optimal unit size as well as the optimal scheduling for both units and
battery charge and discharge (if applicable). The impact of different solar
power profiles and minimum up and down time constraints on the optimal unit and
battery sizes are studied. The battery size required to achieve full solar
energy utilization decreases with the number of units and with increased
flexibility of the units (shorter on and off-time). A novel formulation is
introduced to model quasi-dynamic units that gradually start and stop and the
quasi-dynamic units increase solar energy utilization. The model can also be
applied to search for the optimal number of units for a given cost function.Comment: 6 pages, 3 figures, accepted at The IEEE Conference on Control
Applications (CCA
- âŠ