Search results for " .Production"
showing 10 items of 41 documents
Hydropower Optimization Using Deep Learning
2019
This paper demonstrates how deep learning can be used to find optimal reservoir operating policies in hydropower river systems. The method that we propose is based on the implicit stochastic optimization (ISO) framework, using direct policy search methods combined with deep neural networks (DNN). The findings from a real-world two-reservoir hydropower system in southern Norway suggest that DNNs can learn how to map input (price, inflow, starting reservoir levels) to the optimal production pattern directly. Due to the speed of evaluating the DNN, this approach is from an operational standpoint computationally inexpensive and may potentially address the long-standing problem of high dimension…
Non-dominated “trade-off” solutions in television scheduling optimization
2014
The main approaches for the television scheduling design are commonly based on the ratings or revenues maximization objective, and thus, only a single optimal solution can be obtained, corresponding to the best result for the considered objective. Therefore, these approaches lead up to the alternative solutions loss which, even if less effective from the ratings or revenues maximization viewpoint, may be more suitable for the decision maker because of better compromise in relation to factors influencing the decision process. Specifically, such a compromise could be achieved through a suitable “trade-off” between these factors, with reference to the decision context in which the decision mak…
Simultaneous Airline Scheduling
2008
Currently, there are no solution approaches available to construct and optimize airline schedules within a single model. All existing approaches decompose the problem into smaller and less complex subproblems and solve those subproblems separately. This chapter presents a metaheuristic for simultaneous airline scheduling where several different subproblems are integrated into one single optimization model, except for crew scheduling. The problem-specific metaheuristic uses an adaptive procedure for operator selection to allow an efficient choice between a variety of different operators. Experiments are conducted as proof-of-concept and to calibrate free parameters. Comparing different searc…
Partially Renewable Resources
2014
In recent years, in the field of project scheduling the concept of partially renewable resources has been introduced. Theoretically, it is a generalization of both renewable and non-renewable resources. From an applied point of view, partially renewable resources allow us to model a large variety of situations that do not fit into classical models, but can be found in real problems in timetabling and labor scheduling. In this chapter we define this type of resource, describe an integer linear formulation and present some examples of conditions appearing in real problems which can be modeled using partially renewable resources. Then we introduce some preprocessing procedures to identify infe…
Scheduling Multimodal Transportation Systems
2004
Abstract In this paper a Lagrangian based heuristic procedure for scheduling transportation networks is presented. The solution procedure schedules a single line at a time, possibly correcting the previous decisions at each step.
Selecting Genetic Operators to Maximise Preference Satisfaction in a Workforce Scheduling and Routing Problem
2017
The Workforce Scheduling and Routing Problem (WSRP) is a combinatorial optimisation problem that involves scheduling and routing of workforce. Tackling this type of problem often requires handling a considerable number of requirements, including customers and workers preferences while minimising both operational costs and travelling distance. This study seeks to determine effective combinations of genetic operators combined with heuristics that help to find good solutions for this constrained combinatorial optimisation problem. In particular, it aims to identify the best set of operators that help to maximise customers and workers preferences satisfaction. This paper advances the understand…
Seed Activation Scheduling for Influence Maximization in Social Networks
2018
This paper addresses the challenge of strategically maximizing the influence spread in a social network, by exploiting cascade propagators termed “seeds”. It introduces the Seed Activation Scheduling Problem (SASP) that chooses the timing of seed activation under a given budget, over a given time horizon, in the presence/absence of competition. The SASP is framed as a blogger-centric marketing problem on a two-level network, where the decisions are made to buy sponsored posts from prominent bloggers at calculated points in time. A Bayesian evidence diffusion model – the Partial Parallel Cascade (PPC) model – allows the network nodes to be partially activated, proportional to their accumulat…
Multi-Objective and Multi-Criteria Analysis for Optimal Pump Scheduling in Water Systems
2018
This contribution focuses on the problem of optimal pump scheduling, a fundamental element in pursuing operation optimization of water distribution systems. A combined approach of multi-objective optimization and multi-criteria analysis is herein suggested to first find the Pareto front of non-dominated solutions and then to rank them based on a set of weighted criteria. The Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve the multi-objective problem, while the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to achieve the final ranking.
Autonomous agent system using dispatching rules in the negotiation protocol
2002
In this paper, the most important results obtained by the simulated application of autonomous agent paradigms to a. real factory are presented. The classical rules of dispatching are compared with the autonomous agents approach. In particular, the possibility of redesigning the negotiation rules in terms of currency in order to take into account even non-time-related costs is considered. Finally, a new project on the effective application of the autonomous agent system to a test bed, modelling a simplified firm, is proposed.
AN OBJECT ORIENTED MODEL FOR SCHEDULING IN AGILE MANUFACTURING
2002
Agility represents a key factor in industry to handle the continuous market changes. Companies must re-organize their activities to be agile and competitive in such a dynamic environment. In particular, production planning and control tools are very important to optimize the manufacturing process responsiveness to sudden changes in customer demand. In this paper, an attempt has been made to develop an object-oriented software architecture that allows the optimal line organization to be determined once a set of parts to be produced has been ordered. An optimization module represented by a simulated annealing algorithm has been interfaced with an object oriented architecture to build up a fr…