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constraint programming approaches to disassembly line balancing problem with sequencing decisions

COMPUTERS & OPERATIONS RESEARCH 2021年 126卷 105111-105111页

作者： Edis, Emrah B. Manisa Celal Bayar Univ Dept Ind Engn TR-45140 Manisa Turkey

Recovery of products has received much attention in the last decade due to the increase in both environmental awareness and regulations enacted by governments. In product recovery, disassembly of a product into its constituent parts on a line is one of the most significant operations. This paper deals with a disassembly line balancing and sequencing (DLBS) problem subject to balancing issues, hazardousness of parts, demand quantities and direction changes considered in a lexicographic order. Due to the combinatorial nature of this problem, exact methods, e.g., mixed integer linear programming (MILP), are able to solve only small and medium size problems. Therefore, various metaheuristic algorithms are proposed in literature to find near-optimal solutions. In this paper, constraint programming (CP), which is a suitable technique especially for highly-constrained discrete problems, is used to develop models and solution approaches. To the best of author's knowledge, this study is the first that uses CP for the disassembly line balancing problems. For the DLBS problem, first, a generic CP model is developed. This CP model provides efficient results for small/medium size disassembly problems and benchmark instances. Observing that the generic CP model could not produce even feasible sequence of tasks for some large-sized benchmark instances, a CP-based solution approach is proposed. This approach generates a feasible sequence subject to a fixed assignment of tasks to the workstations by using a CP model and uses this sequence as an initial feasible solution within a warm-start context in CP sequencing models. The computational results show that the proposed CP model improves the several best solutions of medium-sized benchmark instances, while the proposed CP-based solution approach produces excellent results in all large test instances by either improving the best solutions (found so far) or establishing new benchmark solutions. (C) 2020 Elsevier Ltd. All rights reserv

关键词： Disassembly line balancing Sequencing constraint programming Warm-start

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CoPTIC: constraint programming Translated Into C 29th

CoPTIC: Constraint Programming Translated Into C

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29th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS)

作者： Lester, Martin Mariusz Univ Reading Reading Berks England

ISBN: (纸本)9783031308192;9783031308208

constraint programming systems allow a diverse range of problems to be modelled and solved. Most systems require the user to learn a new constraint programming language, which presents a barrier to novice and casual users. To address this problem, we present the CoPTIC constraint programming system, which allows the user to write a model in the well-known programming language C, augmented with a simple API to support using a guess-and-check paradigm. The resulting model is at most as complex as an ordinary C program that uses naive brute force to solve the same problem. CoPTIC uses the bounded model checker CBMC to translate the model into a SAT instance, which is solved using the SAT solver CaDiCaL. We show that, while this is less efficient than a direct translation from a dedicated constraint language into SAT, performance remains adequate for casual users. CoPTIC supports constraint satisfaction and optimisation problems, as well as enumeration of multiple solutions. After a solution has been found, CoPTIC allows the model to be run with the solution;this makes it easy to debug a model, or to print the solution in any desired format.

关键词： constraint programming bounded model checking C programming language

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Cloud Service Matchmaking using constraint programming 24

Cloud Service Matchmaking using Constraint Programming

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IEEE 24th International Conference on Enabling Technologies Infrastructures for Collaborative Enterprises

作者： Zilci, Begum Ilke Slawik, Mathias Kuepper, Axel Tech Univ Berlin Serv Centr Networking Berlin Germany

ISBN: (纸本)9781467376921

Service requesters with limited technical knowledge should be able to compare services based on their quality of service (QoS) requirements in cloud service marketplaces. Existing service matching approaches focus on QoS requirements as discrete numeric values and intervals. The analysis of existing research on non-functional properties reveals two improvement opportunities: list-typed QoS properties as well as explicit handling of preferences for lower or higher property values. We develop a concept and constraint models for a service matcher which contributes to existing approaches by addressing these issues using constraint solvers. The prototype uses an API at the standardisation stage and discovers implementation challenges. This paper concludes that constraint solvers provide a valuable tool to solve the service matching problem with soft constraints and are capable of covering all QoS property types in our analysis. Our approach is to be further investigated in the application context of cloud federations.

关键词： Service matchmaking Service matching Cloud Service marketplaces constraint programming

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A constraint programming approach to tool allocation and production scheduling in flexible manufacturing systems

A constraint programming approach to tool allocation and pro...

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19th International Conference on Flexible Automation and Intelligent Manufacturing

作者： Zeballos, L. J. Univ Nacl Litoral Fac Ingn Quim Dept Ingn Ind RA-3000 Santa Fe Argentina Univ Nacl Litoral INTEC CONICET RA-3000 Santa Fe Argentina

This paper presents a constraint programming (CP) methodology to deal with the scheduling of flexible manufacturing systems (FMSs). The proposed approach, which consists of both a model and a search strategy, handles several features found in industrial environments, such as limitations on number of tools in the system, lifetime of tools, as well as tool magazine capacity of machines. In addition, it tackles the problem in a integrated way by considering tool planning and allocation, machine assignment, part routing, and task timing decisions altogether in the approach. The formulation, which is able to take into account a variety of objective functions, has been successfully applied to the solution of test problems of various sizes and degrees of difficulty. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： constraint programming Flexible manufacturing systems Scheduling Tool management

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Automated Modelling and Solving in constraint programming 24

Automated Modelling and Solving in Constraint Programming

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24th AAAI Conference on Artificial Intelligence (AAAI)

作者： O'Sullivan, Barry Univ Coll Cork Dept Comp Sci Cork Constraint Computat Ctr Cork Ireland

ISBN: (纸本)9781577354635

constraint programming can be divided very crudely into modeling and solving. Modeling defines the problem, in terms of variables that can take on different values, subject to restrictions (constraints) on which combinations of variables are allowed. Solving finds values for all the variables that simultaneously satisfy all the constraints. However, the impact of constraint programming has been constrained by a lack of "user-friendliness". constraint programming has a major "declarative" aspect, in that a problem model can be handed off for solution to a variety of standard solving methods. These methods are embedded in algorithms, libraries, or specialized constraint programming languages. To fully exploit this declarative opportunity however, we must provide more assistance and automation in the modeling process, as well as in the design of application-specific problem solvers. Automated modelling and solving in constraint programming presents a major challenge for the artificial intelligence community. Artificial intelligence, and in particular machine learning, is a natural field in which to explore opportunities for moving more of the burden of constraint programming from the user to the machine. This paper presents technical challenges in the areas of constraint model acquisition, formulation and reformulation, synthesis of filtering algorithms for global constraints, and automated solving. We also present the metrics by which success and progress can be measured.

关键词： constraint programming

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Model Expansion in the Presence of Function Symbols Using constraint programming

Model Expansion in the Presence of Function Symbols Using Co...

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25th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： De Cat, Broes Bogaerts, Bart Devriendt, Jo Denecker, Marc Katholieke Univ Leuven Dept Comp Sci Leuven Belgium

ISBN: (纸本)9781479929719

The traditional approach to Model Expansion (MX) is to reduce the theory to a propositional language and apply a search algorithm to the resulting theory. Function symbols are typically replaced by predicate symbols representing the graph of the function, an operation that blows up the reduced theory. In this paper, we present an improved approach to handle function symbols in a ground-and-solve methodology, building on ideas from constraint programming. We do so in the context of FO(.)(IDP), the knowledge representation language that extends First-Order Logic (FO) with, among others, inductive definitions, arithmetic and aggregates. An MX algorithm is developed, consisting of (i) a grounding algorithm for FO(.)(IDP), parametrised by the function symbols allowed to occur in the reduced theory, and (ii) a search algorithm for unrestricted, ground FO(.)(IDP). The ideas are implemented in the IDP knowledge-base system and experimental evaluation shows that both more compact groundings and improved search performance are obtained.

关键词： Model Expansion constraint programming Knowledge Representation Grounding

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Optimal Beacon Placement for Indoor Positioning Using constraint programming 19

Optimal Beacon Placement for Indoor Positioning Using Constr...

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19th IEEE/ACS International Conference on Computer Systems and Applications (AICCSA)

作者： Loeffler, Sven Kroll, Franz Becker, Ilja Hofstedt, Petra Brandenburg Tech Univ Cottbus Programming Languages & Compiler Construct Cottbus Germany

ISBN: (纸本)9798350310085

Indoor location is a growing topic for hospitals, retirement homes and in case of emergency. For the resource efficient (indoor) positioning of mobile individuals an optimized distribution of the used sensors is necessary. The placement of beacons (sensors) in a building (indoor positioning) can be a difficult and laborious task, especially if done by hand. Multiple researchers already tried to tackle this problem using different algorithms and under the consideration of distinct use cases. However, none of the currently known methods incorporate constraint programming by using only Boolean variables. In this paper we tried to develop a new method for an efficient placement of Bluetooth Low Energy (BLE) beacons in an indoor scenario. More specifically, we try to optimize the beacons for a trilateration algorithm used for indoor positioning. This algorithm requires that three beacons should be in range for every possible position in the building. In a next step the initially calculated beacon positions are further optimized. This is done by trying to reduce the number of beacons used. Afterwards we evaluate the quality of the beacon placements by comparing it against a manually optimized beacon placement and evaluating it in an existing building by checking the quality of multiple sample positions.

关键词： Beacon Placement constraint programming Indoor Positioning Trilateration Combinatorial Optimization Local and Global Search IoTs CSP SAT

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A constraint programming Approach to Multi-Robot Task Allocation and Scheduling in Retirement Homes 22nd

A Constraint Programming Approach to Multi-Robot Task Alloca...

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22nd International Conference on the Principles and Practice of constraint programming (CP)

作者： Booth, Kyle E. C. Nejat, Goldie Beck, J. Christopher Univ Toronto Dept Mech & Ind Engn Toronto ON M5S 3G8 Canada

ISBN: (纸本)9783319449531;9783319449524

We study the application of constraint programming (CP) to the planning and scheduling of multiple social robots interacting with residents in a retirement home. The robots autonomously organize and facilitate group and individual activities among residents. The application is a multi-robot task allocation and scheduling problem in which task plans must be determined that integrate with resident schedules. The problem involves reasoning about disjoint time windows, inter-schedule task dependencies, user and robot travel times, as well as robot energy levels. We propose mixed-integer programming (MIP) and CP approaches for this problem and investigate methods for improving our initial CP approach using symmetry breaking, variable ordering heuristics, and large neighbourhood search. We introduce a relaxed CP model for determining provable bounds on solution quality. Experiments indicate substantial superiority of the initial CP approach over MIP, and subsequent significant improvements in the CP approach through our manipulations. This work is one of the few, of which we are aware, that applies CP to multi-robot task allocation and scheduling problems. Our results demonstrate the promise of CP scheduling technology as a general optimization infrastructure for such problems.

关键词： constraint programming

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A constraint programming Approach for Aircraft Disassembly Scheduling 1

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21st International Conference on the Integration of constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Thomas, Charles Schath, Pierre UCLouvain Ottignies Belgium

ISBN: (数字)9783031605994

ISBN: (纸本)9783031606014;9783031605994

The dismantling and recycling of aircrafts is one of the future challenges for the air transport industry in terms of sustainability. This problem is hard to solve and optimize as planning operations are highly constrained. Indeed, extracting each part requires technicians with the necessary qualifications and equipment. The parts to be extracted are constrained by precedence relations and the number of simultaneous technicians on specific zones is restricted. It is also essential to avoid unbalancing the aircraft during disassembly. Cost is a significant factor, influenced by the duration of ground mobilization and the choice of technicians for each operation. This paper presents a first constraint programming model for this problem using optional interval variables. This model is used to solve variations of a large instance involving up to 1500 tasks, based on real-life data provided by our industrial partner. The results show that the model can find feasible solutions for all variations of the instance and compares the solutions obtained to lower bounds.

关键词： Aircraft Dismantling Scheduling RCPSP constraint programming Application Industrial Problem

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Using constraint programming and local search methods to solve vehicle routing problems 4th

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4th International Conference on Principles and Practice of constraint programming (CP 98)

作者： Shaw, P ILOG SA F-94253 Gentilly France Univ Strathclyde Dept Comp Sci Glasgow G1 1XQ Lanark Scotland

ISBN: (纸本)3540652248

We use a local search method we term Large Neighbourhood Search (LNS) to solve vehicle routing problems. LNS is analogous to the shuffling technique of job-shop scheduling, and so meshes well with constraint programming technology. LNS explores a large neighbourhood of the current solution by selecting a number of "related" customer visits to remove from the set of planned routes. and re-inserting these visits using a constraint-based tree search. Unlike similar methods, we use Limited Discrepancy Search during the tree search to re-insert visits. We analyse the performance of our method on benchmark problems. We demonstrate that results produced are competitive with Operations Research meta-heuristic methods. indicating that constraint-based technology is directly applicable to vehicle routing problems.

关键词： constraint programming

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