In this paper, we study flexible mixed model assembly lines with serially connected stages where stages may have one or more parallel stations. Station parallelism in flexible mixed model assembly lines improves syste...
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In this paper, we study flexible mixed model assembly lines with serially connected stages where stages may have one or more parallel stations. Station parallelism in flexible mixed model assembly lines improves system reliability and enables rapid adaptability to customer demand fluctuations. In this paper we consider task assignment, model and task scheduling problems simultaneously. Due to its success in solving combinatorial problems, we develop a constraint programming model for the problem and test its performance using various size instances. The results reveal that, the model outperforms a Mixed Integer programming model and a decomposition scheme given in the literature.
Timed Petri Nets are a good modeling framework to express the behavior of discrete event systems, such as transport or manufacturing systems. They allow to represent easily the distribution of tasks within a complex s...
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Timed Petri Nets are a good modeling framework to express the behavior of discrete event systems, such as transport or manufacturing systems. They allow to represent easily the distribution of tasks within a complex system, with the capacity to handle time constraints on the duration of these tasks. However, when synchronization is needed between several layers of the system, such models suffer from a lack of mechanisms to identify the components that are handled. Thus, it is difficult to obtain firing sequences avoiding confusion of tokens when activation or coordination patterns are used. Such issues are well addressed with High Level Petri Nets, like Colored PNs where data structures are attached to tokens, allowing to represent a complex behaviour while keeping a compact PN model. However, such models introduce a modeling material that makes it difficult to use direct incremental solving approaches like mathematical or constraint programming, i.e. approaches that do not need to unfold the net and build its whole reachability graph. In this paper, we propose to extend the expressivity of Timed Petri Nets by associating integer identifiers with tokens. Such approach can avoid the confusion of parts in a plant, or trains in a railway network, and allow to model much more possible coordination situations. A constraint programming model is built to follow this new firing semantics, and benchmarks are given to assess its efficiency.
In this paper, we propose to use a constraint programming approach to address the reachability problem in Timed Petri Nets (TPNs). TPNs can be used to model a wide class of systems, from manufacturing issues to formal...
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In this paper, we propose to use a constraint programming approach to address the reachability problem in Timed Petri Nets (TPNs). TPNs can be used to model a wide class of systems, from manufacturing issues to formal verification of embedded systems. Many of the considered problems can be modeled as reachability problems in TPNs. To reduce the space state explosion brought by the exploration of the TPN behavior, we propose to follow the incremental methodology proposed by Bourdeaud'huy and Hanafi (2006), who translate the reachability graph of Timed PNs into a mathematical model. We improve this model by adding valid inequalities and search for solutions using constraint programming (CP). More particularly, we compare different labeling strategies and assess their respective efficiency.
Currently, given the complexity of industrial problems, a powerful software is required to solve constraint Satisfaction Problems. The constraint solvers are a kind of software that are based on a constraint approach....
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ISBN:
(纸本)9783319915210;9783319915203
Currently, given the complexity of industrial problems, a powerful software is required to solve constraint Satisfaction Problems. The constraint solvers are a kind of software that are based on a constraint approach. During the last years many constraint solvers have been created, some of them are intricate software and others are libraries to extend the features of a programming language. There are few efforts to have a framework that allows to compare a constraint system and less to allow the usability analysis of the solvers. In most cases, the users of these systems are more concerned about the number of enumeration and propagation strategies that can be used instead of the ease of use of constraint solvers. This paper presents a framework to compare and obtain a simple and objective analysis of the usability of these kind of systems. The paper shows that it is possible to establish comparison in terms of usability, allowing an analysis beyond the simple comparison of their internal strategies.
Linear constraints are widely used in the modeling of many practical problems, and the solving technologies have important applications in satisfiability modulo theories, program analysis and verification. The efficie...
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ISBN:
(纸本)9783319992471;9783319992464
Linear constraints are widely used in the modeling of many practical problems, and the solving technologies have important applications in satisfiability modulo theories, program analysis and verification. The efficiency of solving procedure could be improved by taking advantages of the relations among constraints. Traditional methods find relations through search, which do not take advantage of the structural characteristics and cost too much time. In this paper, a heuristic based on community division is proposed for finding relations among linear constraints. Firstly it builds a relation graph, which maps each constraint to a node. Then a division tool is employed to divide the nodes into several communities. At last, it tries to find relations among constraints in the same community through search. Experimental results show that the algorithm can effectively process large set of constraints, reduce time cost and find relations with higher quality.
Placer is a model-based tool that, given a model of heterogeneous (or at least multi-core) hardware and a task-based complex software, finds a mapping of the software tasks on the various processing elements of the ha...
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ISBN:
(纸本)9781450359658
Placer is a model-based tool that, given a model of heterogeneous (or at least multi-core) hardware and a task-based complex software, finds a mapping of the software tasks on the various processing elements of the hardware, together with a routing of the transmissions on the available busses, and provides a schedule for the tasks and transmissions. The mapping can minimize either the run time, energy consumption, or both in a multi-objective fashion. The tool combines an Eclipse front-end and a web-service placement back-end based on the OscaR constraint programming library. The tool demonstration illustrates how to build the task model, perform the analysis and possibly iterate to improve the placement.
Optimizing compilers require sophisticated program analysis and transformations to exploit modern hardware. Implementing the appropriate analysis for a compiler optimization is a time consuming activity. For example, ...
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ISBN:
(纸本)9781450356442
Optimizing compilers require sophisticated program analysis and transformations to exploit modern hardware. Implementing the appropriate analysis for a compiler optimization is a time consuming activity. For example, in LLVM, tens of thousands of lines of code are required to detect appropriate places to apply peephole optimizations. It is a barrier to the rapid prototyping and evaluation of new optimizations. In this paper we present the Compiler Analysis Description Language (CAnDL), a domain specific language for compiler analysis. CAnDL is a constraint based language that operates over LLVM's intermediate representation. The compiler developer writes a CAnDL program, which is then compiled by the CAnDL compiler into a C++ LLVM pass. It provides a uniform manner in which to describe compiler analysis and can be applied to a range of compiler analysis problems, reducing code length and complexity. We implemented and evaluated CAnDL on a number of real world use cases: eliminating redundant operations;graphics code optimization;identifying static control flow regions. In all cases were we able to express the analysis more briefly than competing approaches.
This paper presents a new approach to solve rostering, planning and resource management problems. This is achieved by transforming several kinds of finite domain constraints of a given constraint satisfaction problem ...
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ISBN:
(纸本)9783319920078;9783319920061
This paper presents a new approach to solve rostering, planning and resource management problems. This is achieved by transforming several kinds of finite domain constraints of a given constraint satisfaction problem (CSP) into a set of regular membership constraints;and then these regular membership constraints are combined together to a more specific regular membership constraint. The purpose of this approach is to improve the speed of CSPs resolution and to remove undesirable redundant constraints (constraints which slow down the resolution speed) by replacing part of or all constraints of a CSP with a set of regular membership constraints followed by the combination of multiple regular membership constraints into a new, more precise regular membership constraint. A concise rostering example has demonstrated that our approach enables a significant improvement of the performance of the CSP resolution due to the pruning of the search tree.
Large neighbourhood search, a meta-heuristic, has proven to be successful on a wide range of optimisation problems. The algorithm repeatedly generates and searches through a neighbourhood around the current best solut...
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ISBN:
(数字)9783319983349
ISBN:
(纸本)9783319983349;9783319983332
Large neighbourhood search, a meta-heuristic, has proven to be successful on a wide range of optimisation problems. The algorithm repeatedly generates and searches through a neighbourhood around the current best solution. Thus, it finds increasingly better solutions by solving a series of simplified problems, all of which are related to the current best solution. In this paper, we show that significant benefits can be obtained by simulating local-search behaviour in constraint programming by using phase saving based on the best solution found so far during the search, activity-based search (VSIDS), and nogood learning. The approach is highly effective despite its simplicity, improving the highest scoring solver, Chuffed, in the free category of the MiniZinc Challenge 2017, and can be easily integrated into modern constraint programming solvers. We validated the results on a wide range of benchmarks from the competition library, comparing against seventeen state-of-the-art solvers.
We consider a well known resource allocation and scheduling problem for which different approaches like mixed-integer programming (MIP), constraint programming (CP), constraint integer programming (CIP), logic-based B...
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ISBN:
(纸本)9783319930312;9783319930305
We consider a well known resource allocation and scheduling problem for which different approaches like mixed-integer programming (MIP), constraint programming (CP), constraint integer programming (CIP), logic-based Benders decompositions (LBBD) and SAT-modulo theories (SMT) have been proposed and experimentally compared in the last decade. Thanks to the recent improvements in CP Optimizer, a commercial CP solver for solving generic scheduling problems, we show that a standalone tiny CP model can out-perform all previous approaches and close all the 335 instances of the benchmark. The article explains which components of the automatic search of CP Optimizer are responsible for this success. We finally propose an extension of the original benchmark with larger and more challenging instances.
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