8,470 research outputs found
Combining constraint satisfaction and local improvement algorithms to construct anaesthetists' rotas
A system is described which was built to compile weekly rotas for the anaesthetists in a large hospital. The rota compilation problem is an optimization problem (the number of tasks which cannot be assigned to an anaesthetist must be minimized) and was formulated as a constraint satisfaction problem (CSP). The forward checking algorithm is used to find a feasible rota, but because of the size of the problem, it cannot find an optimal (or even a good enough) solution in an acceptable time. Instead, an algorithm was devised which makes local improvements to a feasible solution. The algorithm makes use of the constraints as expressed in the CSP to ensure that feasibility is maintained, and produces very good rotas which are being used by the hospital involved in the project. It is argued that formulation as a constraint satisfaction problem may be a good approach to solving discrete optimization problems, even if the resulting CSP is too large to be solved exactly in an acceptable time. A CSP algorithm may be able to produce a feasible solution which can then be improved, giving a good, if not provably optimal, solution
Conditional constraint satisfaction and configuration: A win-win proposition
Over the years, a whole sector of AI dealing with configuration problems has emerged, and since 1996, an annual configuration workshop has been held in affiliation with a major AI conference. This installment of Trends & Controversies presents essays from the configuration workshop held in August 2006 as part of ECAI in Riva del Garda, Italy
Translation-based Constraint Answer Set Solving
We solve constraint satisfaction problems through translation to answer set
programming (ASP). Our reformulations have the property that unit-propagation
in the ASP solver achieves well defined local consistency properties like arc,
bound and range consistency. Experiments demonstrate the computational value of
this approach.Comment: Self-archived version for IJCAI'11 Best Paper Track submissio
A CSP model for simple non-reversible and parallel repair plans
Thiswork presents a constraint satisfaction problem
(CSP) model for the planning and scheduling of disassembly
and assembly tasks when repairing or substituting
faulty parts. The problem involves not only the ordering of
assembly and disassembly tasks, but also the selection of
them from a set of alternatives. The goal of the plan is the minimization
of the total repairing time, and the model considers,
apart from the durations and resources used for the assembly
and disassembly tasks, the necessary delays due to the change
of configuration in the machines, and to the transportation
of intermediate subassemblies between different machines.
The problem considers that sub-assemblies that do not contain
the faulty part are nor further disassembled, but allows
non-reversible and parallel repair plans. The set of all feasible
repair plans are represented by an extended And/Or graph.
This extended representation embodies all of the constraints
of the problem, such as temporal and resource constraints and
those related to the selection of tasks for obtaining a correct
plan.Ministerio de Educación y Ciencia DIP2006-15476-C02-0
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