181 research outputs found
Optimizing production scheduling of steel plate hot rolling for economic load dispatch under time-of-use electricity pricing
Time-of-Use (TOU) electricity pricing provides an opportunity for industrial
users to cut electricity costs. Although many methods for Economic Load
Dispatch (ELD) under TOU pricing in continuous industrial processing have been
proposed, there are still difficulties in batch-type processing since power
load units are not directly adjustable and nonlinearly depend on production
planning and scheduling. In this paper, for hot rolling, a typical batch-type
and energy intensive process in steel industry, a production scheduling
optimization model for ELD is proposed under TOU pricing, in which the
objective is to minimize electricity costs while considering penalties caused
by jumps between adjacent slabs. A NSGA-II based multi-objective production
scheduling algorithm is developed to obtain Pareto-optimal solutions, and then
TOPSIS based multi-criteria decision-making is performed to recommend an
optimal solution to facilitate filed operation. Experimental results and
analyses show that the proposed method cuts electricity costs in production,
especially in case of allowance for penalty score increase in a certain range.
Further analyses show that the proposed method has effect on peak load
regulation of power grid.Comment: 13 pages, 6 figures, 4 table
Production Scheduling in Integrated Steel Manufacturing
Steel manufacturing is both energy and capital intensive, and it includes multiple production stages, such as iron-making, steelmaking, and rolling. This dissertation investigates the order schedule coordination problem in a multi-stage manufacturing context. A mixed-integer linear programming model is proposed to generate operational (up to the minute) schedules for the steelmaking and rolling stages simultaneously. The proposed multi-stage scheduling model in integrated steel manufacturing can provide a broader view of the cost impact on the individual stages. It also extends the current order scheduling literature in steel manufacturing from a single-stage focus to the coordinated multi-stage focus. Experiments are introduced to study the impact of problem size (number of order batches), order due time and demand pattern on solution performance. Preliminary results from small data instances are reported. A novel heuristic algorithm, Wind Driven Algorithm (WDO), is explained in detail, and numerical parameter study is presented. Another well-known and effective heuristic approach based on Particle Swarm Optimization (PSO) is used as a benchmark for performance comparison. Both algorithms are implemented to solve the scheduling model. Results show that WDO outperforms PSO for the proposed model on solving large sample data instances. Novel contributions and future research areas are highlighted in the conclusion
"Rotterdam econometrics": publications of the econometric institute 1956-2005
This paper contains a list of all publications over the period 1956-2005, as reported in the Rotterdam Econometric Institute Reprint series during 1957-2005.
"Rotterdam econometrics": publications of the econometric institute 1956-2005
This paper contains a list of all publications over the period 1956-2005, as reported in the Rotterdam Econometric Institute Reprint series during 1957-2005
Aeronautical Engineering. A continuing bibliography, supplement 115
This bibliography lists 273 reports, articles, and other documents introduced into the NASA scientific and technical information system in October 1979
The bi-objective travelling salesman problem with profits and its connection to computer networks.
This is an interdisciplinary work in Computer Science and Operational Research. As it is
well known, these two very important research fields are strictly connected. Among other
aspects, one of the main areas where this interplay is strongly evident is Networking. As far
as most recent decades have seen a constant growing of every kind of network computer connections,
the need for advanced algorithms that help in optimizing the network performances
became extremely relevant. Classical Optimization-based approaches have been deeply studied
and applied since long time. However, the technology evolution asks for more flexible and
advanced algorithmic approaches to model increasingly complex network configurations. In
this thesis we study an extension of the well known Traveling Salesman Problem (TSP): the
Traveling Salesman Problem with Profits (TSPP). In this generalization, a profit is associated
with each vertex and it is not necessary to visit all vertices. The goal is to determine
a route through a subset of nodes that simultaneously minimizes the travel cost and maximizes
the collected profit. The TSPP models the problem of sending a piece of information
through a network where, in addition to the sending costs, it is also important to consider
what “profit” this information can get during its routing. Because of its formulation, the
right way to tackled the TSPP is by Multiobjective Optimization algorithms. Within this
context, the aim of this work is to study new ways to solve the problem in both the exact
and the approximated settings, giving all feasible instruments that can help to solve it, and
to provide experimental insights into feasible networking instances
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