Constraint Satisfaction Problem Approach Research Articles

A Forward-Checking algorithm based on a Generalised Hypertree Decomposition for solving non-binary constraint satisfaction problems

Methods exploiting hypertree decompositions are considered as the best approach for solving extensional constraint satisfaction problems (CSPs) on finite domains, with regard to theoretical time complexity when fixed widths are considered. However, this result has not been confirmed in practice because of the memory explosion problem. In this article, a new approach for efficient solving extensional non-binary CSPs is proposed. It is a combination of an enumerative search algorithm which is memory efficient and a Generalised Hypertree Decomposition (GHD) that is time efficient. This new approach is a cluster-oriented Forward-Checking algorithm. It considers the solutions of the subproblems deriving from the decomposition, as the values to be assigned rather than the values associated with the variables of the initial problem. In addition, the algorithm is guided by an order induced by the clusters deriving from the GHD. Moreover, two improved versions of this algorithm are proposed. The first version uses nogoods and the second one improves it again by a dynamic reordering of subtrees. All these algorithms have been implemented and the experimental results are promising.

Hybrid Algorithm combining Genetic algorithms and CSP approach to plane an Optimized path for a Mobile Robot moving under Time Window

The problems of optimization are considered as a type of a constraint satisfaction problem: COP (Constraint Optimization problem). In this frame goes our first works which are interested in the optimization of a reference trajectory of a mobile robot used for the surveillance (Surveyor Robot). Indeed, in the previous work we have focused on the minimization of the length of this trajectory by using the approach of the genetic algorithms. At the level of our present researches we shall add temporal windows to limit the time delayed in the passage between one surveyed site and the following one. The consideration of temporal aspects requires a modelling of problem with a satisfaction of constraints. So that, a hybridization of the algorithm of optimization already developed at the previous work by the approach of CSP (Constraint Satisfaction Problem), is indispensable for our case. The new algorithm which will be developed and feigned at this work is a genetic algorithm allowing minimizing the length of a trajectory crossed by a mobile robot of surveillance by respecting the time fixed to take during the passage through two successive sites. Keywords-Constraint Satisfaction Problem, Genetic algorithms, Meta-heuristics, Mobile Robot, Neighbourhood method, Optimization, Path Tracking.

A constraint-based parametric model to support building services design exploration

In this paper, we present a generative design approach using constraint-based programming to handle the space configuration for ceiling mounted fan coil systems in buildings. This work utilises and builds on the result from previous projects presented in Medjdoub et al. [(2003). Generation of variational standard plant room solutions. Automation in Construction, 12(2), 155–166] and Medjdoub [(2009). Constraint-based adaptation for complex space configuration in building services. ITcon, 14, 724–735.]. In Medjdoub [(2009). Constraint-based adaptation for complex space configuration in building services. ITcon, 14, 724–735], we have presented a hybrid approach using case-based reasoning and constraint satisfaction problem approach to deal with the space configuration and pipe routing of complex design problems for ceiling mounted fan coil systems in buildings. One of the limitations of the aforementioned approach is that the solution generated is defined only geometrically. In this work, we have redefined the case library by describing each case as a graph of design constraints. This new definition of the cases supports the generation of parametric solutions, where further interactive modification can be done by the user while maintaining all the design constraints. This brings benefits in terms of increasing the quality of the solution by providing the user the possibility to make the appropriate modifications using his/her heuristic knowledge. Finally, this approach has been benchmarked using real scenario design projects.

Control and programming of a multi‐robot‐based reconfigurable fixture

PurposeMachining fixtures must fit exactly the work piece to support it appropriately. Even slight change in the design of the work piece renders the costly fixture useless. Substitution of traditional fixtures by a programmable multi‐robot system supporting the work pieces requires a specific control system and a specific programming method enabling its quick reconfiguration. The purpose of this paper is to develop a novel approach to task planning (programming) of the reconfigurable fixture system.Design/methodology/approachThe multi‐robot control system has been designed following a formal approach based on the definition of the system structure in terms of agents and transition function definition of their behaviour. Thus, a modular system resulted, enabling software parameterisation. This facilitated the introduction of changes brought about by testing different variants of the mechanical structure of the system. A novel approach to task planning (programming) of the reconfigurable fixture system has been developed. Its solution is based on constraint satisfaction problem approach. The planner takes into account physical, geometrical, and time‐related constraints.FindingsReconfigurable fixture programming is performed by supplying CAD definition of the work piece. Out of this data the positions of the robots and the locations of the supporting heads are automatically generated. This proved to be an effective programming method. The control system on the basis of the thus obtained plan effectively controls the behaviours of the supporting robots in both drilling and milling operations.Originality/valueThe shop‐floor experiments with the system showed that the work piece is held stiffly enough for both milling and drilling operations performed by the CNC machine. If the number of diverse work piece shapes is large, the reconfigurable fixture is a cost‐effective alternative to the necessary multitude of traditional fixtures. Moreover, the proposed design approach enables the control system to handle a variable number of controlled robots and accommodates possible changes to the hardware of the work piece supporting robots.

Network Load Balancing with Strong Migration in an Agent Based Grid System Using CSP Approach

In this paper we present a dynamic network traffic balancing approach using strong migration on an agent based grid environment. The paper focuses on three different areas, namely load balancing, strong mobility and CSP (Constraint Satisfaction Problem) approach. We use CSP approach for making task migration decisions. Strong task migration is used to move tasks between nodes at runtime to maintain dynamic balancing. Our approach is implemented on an agent based grid system, where all loads can be formulated as weighted constraints of a CSP. We define inter-messaging rates of tasks as the main load of our system. Activated by the results produced by CSP execution, the strong migration mechanism we have integrated into the grid system maintains dynamic traffic balancing by transferring tasks such that frequently communicating tasks end up on the same node and do not consume network bandwidth. Experimental results show remarkable reduction on network use of the grid system.

A Distributed Constraint Satisfaction Problem Approach to Virtual Device Composition

The dynamic composition of networked appliances, or virtual devices, enables users to generate complex, strong, and specific systems. Current MANET-based composition schemes use service discovery mechanisms that depend on periodic service advertising by controlled broadcast, resulting in the unnecessary depletion of node resources. The assumption that, once generated, a virtual device is to remain static is false; the device should gracefully degrade and upgrade along with the conditions in the user's environment, particularly the network's current performance requirements. Presently, schemes for infrastructure-less virtual device composition and management do not consider this adaptation. We present a distributed constraint satisfaction problem (distCSP) for virtual device composition in MANETs that addresses these issues together with simulations that show its effectiveness and efficiency.

Using Constraint Satisfaction Problem approach to solve human resource allocation problems in cooperative health services

In developing countries, the increasing utilization of health services, due to a great life expectancy, is followed by a reduction in incomes from the public health system and from private insurance companies, to the payment of medical procedures. Beyond this scenery, it is mandatory an effective hospital cost control though the utilization of planning tools. This work is intended to contribute to the reduction of hospital costs, proposing a new tool for planning human resources utilization in hospital plants. Specifically, it is proposed a new tool for human resources allocation in health units. The solution to the allocation problem uses the CSP technique (Constraint Satisfaction Problem) associated with the backtracking search algorithm. With the objective of enhancing the backtracking search algorithm performance a new heuristics is proposed. Through some simulations the performance of the proposed heuristics is compared to the other heuristics previously published in literature: remaining minimum values, forward checking and grade heuristics. Another important contribution of this work is the mathematical modeling of the constraints, that could be unary, multiple, numeric and implicit constraints. In the results it is presented a case study of a human resource allocation in a cooperative health service. Based on the results, it is proposed that for a real allocation problems solution, the best approach is to combine the remaining minimum values heuristics with the grade heuristics, to select the best unit allocation to be filled, and then use the proposed heuristic to select the best physician to the chosen unit allocation. This association shows a satisfactory result for the human resource allocation problem of the case study, with an algorithm convergence time of 46.7 min with no backtracks. The same problem when manually resolved took about more than 50 h.

A CSP approach for the network of product lifecycle constraints consistency in a collaborative design context

In this paper, we are considering that the design process can be modelled in the form of a constraint satisfaction problem (CSP). CSP modelling or resolution has proved its efficiency within the framework of single-designer design. We propose to extend the functions of CSP to the context of multi-concept design of the same artefact. We define CoCSP as cooperative constraint satisfaction problem including the actors of the design problem. We are presenting the operating principles of an algorithm for the real-time management of design decisions, based on a model described in the form of a CoCSP for the integration of supply-chain constraints. This algorithm enables the number of design decisions rejected at a given moment in design to be kept to a minimum. The algorithm forms the core of a prototype for an unsupervised, generic constraint-based collaborative design system. Our aim is to produce a platform centred on the notion of constraints that will enable a product design problem to be modelled and solved by integrating supply-chain constraints as far upstream as possible.

Using Decomposition Techniques and Constraint Programming for Solving the Two-Dimensional Bin-Packing Problem

The two-dimensional bin-packing problem is the problem of orthogonally packing a given set of rectangles into a minimum number of two-dimensional rectangular bins. The problem is 𝒩𝒫-hard and very difficult to solve in practice as no good mixed integer programming (MIP) formulation has been found for the packing problem. We propose an algorithm based on the well-known Dantzig-Wolfe decomposition where the master problem deals with the production constraints on the rectangles while the subproblem deals with the packing of rectangles into a single bin. The latter problem is solved as a constraint-satisfaction problem (CSP), which makes it possible to formulate a number of additional constraints that may be difficult to formulate as MIP models. This includes guillotine-cutting requirements, relative positions, fixed positions and irregular bins. The CSP approach uses forward propagation to prune inferior arrangements of rectangles. Unsuccessful attempts to pack rectangles into a bin are brought back to the master model as valid inequalities. Hence, CSP is used not only to solve the pricing problem but also to generate valid inequalities in a branch-and-cut system. Using delayed column-generation, we obtain lower bounds of very good quality in reasonable time. In all instances considered, we obtain similar or better bounds than previously published. Several instances with up to n = 100 rectangles are solved to optimality through the developed branch-and-price-and-cut algorithm.

A Constraint Satisfaction Problem Approach Linking Function and Grammar-Based Design Generation to Assembly

This work presents a constraint satisfaction problem (CSP) approach to design, integrating a function-based design generation algorithm to a geometric modeler. Our long-term goal is to create a unified graph-grammar based designer assistance tool that generates geometrically valid designs from functionally feasible design concepts. This paper introduces the Assembler, a graph-grammar based algorithm that takes a functionally valid but geometrically ambiguous design of a cart made of Meccano Erector Set components and converts it into geometrically valid models of cart designs. Assembler uses grammars to implement solving the CSP formulation of the assembly problem. From the exploration of Assembler’s geometric models, we conclude that the assembly problems of our carts require more sophisticated constraining to generate more realistic designs.