Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial Asociación Española pa... more Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial Asociación Española para la Inteligencia Artificial revista@aepia.org ISSN (Versión impresa): 1137-3601 ISSN (Versión en línea): 1988-3064 ESPAÑA ... AEPIA (http://www.aepia.org/revista). ARTÍCULO ...
... system Frédérique Versteegh · Miguel A. Salido · Adriana Giret ... country. At the lower leve... more ... system Frédérique Versteegh · Miguel A. Salido · Adriana Giret ... country. At the lower level of the system, each RU is represented by a node and arcs are roads connecting RUs (see Fig.6). The system may be composed of millions of RUs. ...
Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2015
ABSTRACT Many real-world problems are known as planning and scheduling problems, where resources ... more ABSTRACT Many real-world problems are known as planning and scheduling problems, where resources must be allocated so as to optimize overall performance objectives. The traditional scheduling models consider performance indicators such as processing time, cost, and quality as optimization objectives. However, most of them do not take into account energy consumption and robustness. We focus our attention in a job-shop scheduling problem where machines can work at different speeds. It represents an extension of the classical job-shop scheduling problem, where each operation has to be executed by one machine and this machine can work at different speeds. The main goal of the paper is focused on the analysis of three important objectives (energy efficiency, robustness, and makespan) and the relationship among them. We present some analytical formulas to estimate the ratio/relationship between these parameters. It can be observed that there exists a clear relationship between robustness and energy efficiency and a clear trade-off between robustness/energy efficiency and makespan. It represents an advance in the state of the art of production scheduling, so obtaining energy-efficient solutions also supposes obtaining robust solutions, and vice versa.
The areas of planning and scheduling (from the Artificial Intelligence point of view) have seen i... more The areas of planning and scheduling (from the Artificial Intelligence point of view) have seen important advances thanks to application of constraint satisfaction techniques. Currently, many important real-world problems require efficient constraint handling for planning, scheduling and resource allocation to competing goal activities over time in the presence of complex state-dependent constraints. Solutions to these problems require integration of resource allocation and plan synthesis capabilities. Hence to manage such complex problems planning, scheduling and constraint satisfaction must be interrelated. This special issue on Constraint Satisfaction for Planning and Scheduling Problems compiles a selection of papers dealing with various aspects of applying constraint satisfaction techniques in planning and scheduling. The core of submitted papers was formed by the extended versions of papers presented at COPLAS’2009: ICAPS 2009 Workshop on Constraint Satisfaction Techniques for...
ABSTRACT The job shop scheduling problem with an additional resource type has been recently propo... more ABSTRACT The job shop scheduling problem with an additional resource type has been recently proposed to model the situation where each operation in a job shop has to be assisted by one of a limited set of human operators. We confront this problem with the objective of minimizing the total flow time, which makes the problem more interesting from a practical point of view and harder to solve than the version with makespan minimization. To solve this problem we propose an enhanced dept-first search algorithm. This algorithm exploits a schedule generation schema termed OG&T, two admissible heuristics and some powerful pruning rules. In order to diversify the search, we also consider a variant of this algorithm with restarts. We have conducted an experimental study across several benchmarks. The results of this study show that the global pruning rules are really effective and that the proposed algorithms are quite competent for solving this problem.
ABSTRACT Decision makers must face the dynamism and uncertainty of real-world environments when t... more ABSTRACT Decision makers must face the dynamism and uncertainty of real-world environments when they need to solve the scheduling problems. Different incidences or breakdowns, for example, initial data could change or some resources could become unavailable, may eventually cause the infeasibility of the obtained schedule. To overcome this issue, a robust model and a proactive approach are presented for scheduling problems without any previous knowledge about incidences. This paper is based on proportionally distributing operational buffers among the tasks. In this paper, we consider the berth allocation problem and the quay crane assignment problem as a representative example of scheduling problems. The dynamism and uncertainty are managed by assessing the robustness of the schedules. The robustness is introduced by means of operational buffer times to absorb those unknown incidences or breakdowns. Therefore, this problem becomes a multiobjective combinatorial optimization problem that aims to minimize the total service time, to maximize the buffer times, and to minimize the standard deviation of the buffer times. To this end, a mathematical model and a new hybrid multiobjective metaheuristic is presented and compared with two well-known multiobjective genetic algorithms: NSGAII and SPEA2+.
Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial Asociación Española pa... more Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial Asociación Española para la Inteligencia Artificial revista@aepia.org ISSN (Versión impresa): 1137-3601 ISSN (Versión en línea): 1988-3064 ESPAÑA ... AEPIA (http://www.aepia.org/revista). ARTÍCULO ...
... system Frédérique Versteegh · Miguel A. Salido · Adriana Giret ... country. At the lower leve... more ... system Frédérique Versteegh · Miguel A. Salido · Adriana Giret ... country. At the lower level of the system, each RU is represented by a node and arcs are roads connecting RUs (see Fig.6). The system may be composed of millions of RUs. ...
Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2015
ABSTRACT Many real-world problems are known as planning and scheduling problems, where resources ... more ABSTRACT Many real-world problems are known as planning and scheduling problems, where resources must be allocated so as to optimize overall performance objectives. The traditional scheduling models consider performance indicators such as processing time, cost, and quality as optimization objectives. However, most of them do not take into account energy consumption and robustness. We focus our attention in a job-shop scheduling problem where machines can work at different speeds. It represents an extension of the classical job-shop scheduling problem, where each operation has to be executed by one machine and this machine can work at different speeds. The main goal of the paper is focused on the analysis of three important objectives (energy efficiency, robustness, and makespan) and the relationship among them. We present some analytical formulas to estimate the ratio/relationship between these parameters. It can be observed that there exists a clear relationship between robustness and energy efficiency and a clear trade-off between robustness/energy efficiency and makespan. It represents an advance in the state of the art of production scheduling, so obtaining energy-efficient solutions also supposes obtaining robust solutions, and vice versa.
The areas of planning and scheduling (from the Artificial Intelligence point of view) have seen i... more The areas of planning and scheduling (from the Artificial Intelligence point of view) have seen important advances thanks to application of constraint satisfaction techniques. Currently, many important real-world problems require efficient constraint handling for planning, scheduling and resource allocation to competing goal activities over time in the presence of complex state-dependent constraints. Solutions to these problems require integration of resource allocation and plan synthesis capabilities. Hence to manage such complex problems planning, scheduling and constraint satisfaction must be interrelated. This special issue on Constraint Satisfaction for Planning and Scheduling Problems compiles a selection of papers dealing with various aspects of applying constraint satisfaction techniques in planning and scheduling. The core of submitted papers was formed by the extended versions of papers presented at COPLAS’2009: ICAPS 2009 Workshop on Constraint Satisfaction Techniques for...
ABSTRACT The job shop scheduling problem with an additional resource type has been recently propo... more ABSTRACT The job shop scheduling problem with an additional resource type has been recently proposed to model the situation where each operation in a job shop has to be assisted by one of a limited set of human operators. We confront this problem with the objective of minimizing the total flow time, which makes the problem more interesting from a practical point of view and harder to solve than the version with makespan minimization. To solve this problem we propose an enhanced dept-first search algorithm. This algorithm exploits a schedule generation schema termed OG&T, two admissible heuristics and some powerful pruning rules. In order to diversify the search, we also consider a variant of this algorithm with restarts. We have conducted an experimental study across several benchmarks. The results of this study show that the global pruning rules are really effective and that the proposed algorithms are quite competent for solving this problem.
ABSTRACT Decision makers must face the dynamism and uncertainty of real-world environments when t... more ABSTRACT Decision makers must face the dynamism and uncertainty of real-world environments when they need to solve the scheduling problems. Different incidences or breakdowns, for example, initial data could change or some resources could become unavailable, may eventually cause the infeasibility of the obtained schedule. To overcome this issue, a robust model and a proactive approach are presented for scheduling problems without any previous knowledge about incidences. This paper is based on proportionally distributing operational buffers among the tasks. In this paper, we consider the berth allocation problem and the quay crane assignment problem as a representative example of scheduling problems. The dynamism and uncertainty are managed by assessing the robustness of the schedules. The robustness is introduced by means of operational buffer times to absorb those unknown incidences or breakdowns. Therefore, this problem becomes a multiobjective combinatorial optimization problem that aims to minimize the total service time, to maximize the buffer times, and to minimize the standard deviation of the buffer times. To this end, a mathematical model and a new hybrid multiobjective metaheuristic is presented and compared with two well-known multiobjective genetic algorithms: NSGAII and SPEA2+.
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