52 research outputs found
Planning and Scheduling of Business Processes in Run-Time: A Repair Planning Example
Over the last decade, the efficient and flexible management of business
processes has become one of the most critical success aspects. Furthermore, there
exists a growing interest in the application of Artificial Intelligence Planning and
Scheduling techniques to automate the production and execution of models of organization.
However, from our point of view, several connections between both
disciplines remains to be exploited. The current work presents a proposal for modelling
and enacting business processes that involve the selection and order of the
activities to be executed (planning), besides the resource allocation (scheduling),
considering the optimization of several functions and the reach of some objectives.
The main novelty is that all decisions (even the activities selection) are taken in
run-time considering the actual parameters of the execution, so the business process
is managed in an efficient and flexible way. As an example, a complex and representative
problem, the repair planning problem, is managed through the proposed
approach.Ministerio de Ciencia e Innovación TIN2009-13714Junta de Andalucía P08-TIC-0409
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
Supporting the Optimized Execution of Business Processes through Recommendations
In order to be able to flexibly adjust a company’s business
processes (BPs) there is an increasing interest in flexible Process-Aware
Information Systems (PAISs). This increasing flexibility, however, typically
implies decreased user guidance by the PAIS and thus poses additional
challenges to its users. This work proposes a recommendation
system which assists users during process execution to optimize performance
goals of the processes. The recommendation system is based on a
constraint-based approach for planning and scheduling the BP activities
and considers both the control-flow and the resource perspective.Ministerio de Ciencia e Innovación TIN2009-1371
A model for assembly sequence planning in a multirobot environment
2002 IFAC15th Triennial World Congress, Barcelona, SpainThis paper presents a model for the selection of optimal assembly sequences for a product in multirobot systems. The objective of the plan is the minimization of the total assembly time (makespan). To meet this objective, the model takes into account, in addition to the assembly times and resources for each task, the times needed to change tools in the robots, and the delays due to the transportation of intermediate subassemblies between different machines. An A* algorithm that solves the problem is also presented, which starts from the And/Or graph for the product (compressed representation of all feasible assembly plans)
A Constraint-based Model for Multi-objective Repair Planning
This work presents a constraint based model for the
planning and scheduling of disconnection and connection
tasks when repairing faulty components in a system.
Since multi-mode operations are considered, the
problem involves the ordering and the selection of the
tasks and modes from a set of alternatives, using the
shared resources efficiently. Additionally, delays due to
change of configurations and transportation are considered.
The goal is the minimization of two objective functions:
makespan and cost. The set of all feasible plans
are represented by an extended And/Or graph, that embodies
all of the constraints of the problem, allowing non
reversible and parallel plans. A simple branch-and-bound
algorithm has been used for testing the model with different
combinations of the functions to minimize using the
weighted-sum approach.Ministerio de Educación y Ciencia DIP2006-15476-C02-0
OptBPPlanner: Automatic Generation of Optimized Business Process Enactment Plans
Unlike imperative models, the specifi cation of business process (BP)
properties in a declarative way allows the user to specify what has to be done instead
of having to specify how it has to be done, thereby facilitating the human work
involved, avoiding failures, and obtaining a better optimization. Frequently, there
are several enactment plans related to a specifi c declarative model, each one
presenting specifi c values for different objective functions, e.g., overall completion
time. As a major contribution of this work, we propose a method for the automatic
generation of optimized BP enactment plans from declarative specifi cations. The
proposed method is based on a constraint-based approach for planning and scheduling
the BP activities. These optimized plans can then be used for different purposes
like simulation, time prediction, recommendations, and generation of optimized BP
models. Moreover, a tool-supported method, called OptBPPlanner, has been implemented
to demonstrate the feasibility of our approach. Furthermore, the proposed
method is validated through a range of test models of varying complexity.Ministerio de Ciencia e Innovación TIN2009-1371
Improving the Computational Efficiency in Symmetrical Numeric Constraint Satisfaction Problems
Models are used in science and engineering for experimentation,
analysis, diagnosis or design. In some cases, they can be considered
as numeric constraint satisfaction problems (NCSP). Many models
are symmetrical NCSP. The consideration of symmetries ensures that
NCSP-solver will find solutions if they exist on a smaller search space.
Our work proposes a strategy to perform it. We transform the symmetrical
NCSP into a newNCSP by means of addition of symmetry-breaking
constraints before the search begins. The specification of a library of possible
symmetries for numeric constraints allows an easy choice of these
new constraints. The summarized results of the studied cases show the
suitability of the symmetry-breaking constraints to improve the solving
process of certain types of symmetrical NCSP. Their possible speedup
facilitates the application of modelling and solving larger and more
realistic problems.Ministerio de Ciencia y Tecnología DIP2003-0666-02-
A Topological-Based Method for Allocating Sensors by Using CSP Techniques
Model-based diagnosis enables isolation of faults of a system.
The diagnosis process uses a set of sensors (observations) and a model
of the system in order to explain a wrong behaviour. In this work, a
new approach is proposed with the aim of improving the computational
complexity for isolating faults in a system. The key idea is the addition of
a set of new sensors which allows the improvement of the diagnosability
of the system. The methodology is based on constraint programming
and a greedy method for improving the computational complexity of the
CSP resolution. Our approach maintains the requirements of the user
(detectability, diagnosability,. . .).Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0
Improving the Evolutionary Coding for Machine Learning Tasks
The most influential factors in the quality of the solutions
found by an evolutionary algorithm are a correct coding of the
search space and an appropriate evaluation function of the potential
solutions. The coding of the search space for the obtaining of decision
rules is approached, i.e., the representation of the individuals of
the genetic population. Two new methods for encoding discrete and
continuous attributes are presented. Our “natural coding” uses one
gene per attribute (continuous or discrete) leading to a reduction in
the search space. Genetic operators for this approached natural coding
are formally described and the reduction of the size of the search
space is analysed for several databases from the UCI machine learning
repository.Comisión Interministerial de Ciencia y Tecnología TIC1143–C03–0
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