Roman Buil

Improvement of Lagrangian Relaxation Convergence for Production Scheduling

It is widely accepted that new production scheduling tools are playing a key role in flexible manufacturing systems to improve their performance by avoiding idleness machines while minimizing set-up times penalties, reducing penalties for do not delivering orders on time, etc. Since manufacturing scheduling problems are NP-hard, there is a need of improving scheduling methodologies to get good solutions within low CPU time. Lagrangian Relaxation (LR) is known for handling large-scale separable problems, however, the convergence to the optimal solution can be slow. LR needs customized parametrization, depending on the scheduling problem, usually made by an expert user. It would be interesting the use of LR without being and expertise, i.e., without difficult parameters tuning. This paper presents innovative approaches on the LR method to be able to develop a tool capable of solve scheduling problems applying the LR method without requiring a deep expertise on it. First approach is the improvement of an already existing method which use Constraint Programming (CP) to obtain better primal cost convergence. Second approach is called Extended Subgradient Information (ESGI) and it speed up the dual cost convergence. Finally, a set of step size rules for the Subgradient (SG) method are compared to choose the most appropriate rule depending on the scheduling problem. Test results demonstrate that the application of CP and ESGI approaches, together with LR and the selected step size rule depending on the problem, generates better solutions than the LR method by itself.

Operational and strategic supply model redesign for an optical chain company using digital simulation

Decision making inside a company is usually performed by means of decision support tools at three different levels (strategic, tactical and operational) according to the working horizon. Unfortunately, the consequences of any decision at the strategic level are propagated to the tactical and even the operational levels. In order to support highly efficient flexibility while avoiding infrastructure over-sizing, resource saturation and poor coordination of activities and resources, it is important to consider the cause—effect interaction of strategic decisions with operational ones. In this paper, a discrete-event system simulation approach to evaluate the influence of the internal interactions among material, people, information and financial resources on the success of a Spanish optician supply chain is introduced. The emergent dynamics are analyzed and a redesign of the business and distribution network is proposed to foster synergy among supply chain actors.

State space analysis for model plausibility validation in multi-agent system simulation of urban policies

Multi-agent system (MAS) models have been increasingly applied to the simulation of complex phenomena in different areas, providing successful and credible results. However, model validation is still an open problem. The complexity of the stochastic interaction between agents, together with a large number of parameters, can make validation procedures intractable. Particular validation difficulties appear in social science using MAS models when agents are defined as spatial objects to computationally represent the behaviour of individuals to study emergent patterns arising from micro-level interactions. This paper considers some of the difficulties in establishing the verification and validation of agent-based models (ABMs) and proposes the use of coloured Petri net (CPN) formalism to specify agent behaviour to check whether the model looks and behaves logically. Model plausibility is used to express the conformity of the model with a priori knowledge about the process. A proof-of-concept is presented by means of a case study to test the robustness of emergent patterns through sensitivity analyses and can be used for model calibration. The proposed methodology has been applied in the European Future Policy Modelling project (www.fupol.eu) to create trust and increase the credibility of the ABMs developed to foster e-participation in the design of urban policies by means of simulation techniques.

The Yantai Urban Economic Development Assessment Simulator

Economic development simulation is an important component of policy crafting. The possibility of testing potential solutions and selecting the most applicable is the basis of successful development. The article deals with the Yantai Urban Economic Development Assessment simulator, which is based on a multi agent-based (ABM/MAS) simulation model that is comprised of the resource consumption function minimization algorithm. The aim of the simulation is to rank industries in conformity with resource consumption, influence on the environment and income paid into the budget of the city. The simulator allows the administration of the city to elaborate justified decisions about the promotion of successful enterprises and the closing unsatisfactory ones.

Multi-agent system simulation for urban policy design: open space land use change problem

Multi-agent system (MAS) models have been increasingly applied to the simulation of complex phenomena in different areas, providing successful and credible results. Citizens behavior related to a specific urban activity (i.e., recreation activities in a park, using bicycle for mobility purposes) can be modeled as an agent (actor) with several affinities and preferences which are dependent on aspects that affect the activity. A particular application of a MAS approach is in area of urban policy design, in which policies should be designed considering citizens needs, preferences and behavior. Once an open space in a city is available (i.e., an industry is moved to an industrial area), a land use policy should contribute to identify the new use for the urban space. There are different land use policies that can be applied depending on which services or facilities must be empowered in the city. It is important to identify the correct policy in order to satisfy present citizens needs but considering also the future needs in a social changing context. A socio-technological simulation model has been developed to allow citizens to get a better understanding of the urban problem, its dynamics and explore the sustainability of the different solutions., enhancing citizens to participate in the urban decisions through new technologies (i.e., e-participation). This paper illustrates an open space MAS simulation model for land use design policies in which citizens can check their opinion and get a better understanding of the different choices and its acceptability by the community considering not only present neighborhood profiles, but also future neighborhood configurations. It is the first step before the development of the final software including a user friendly interface to let citizens with different cultural profiles to perform simulations as an essential and neutral tool to reach consensus during the decision-making process in urban policy design.

Specification of CPN models into MAS platform for the modelling of social policy issues: FUPOL project

Simulation transparency is becoming more crucial in the decision making process when quantitative computer tools are used to justify some strategies. The coloured petri net (CPN) formalism is a promising modelling approach to foster simulation transparency by means of state space traceability tools, which have been proven to be useful for modelling system dynamics with conflict patterns. E-governance is one of these areas in which the use of a multi agent system (MAS) to represent social dynamics in a certain urban context could be used to engage citizens in the design of urban policies that affects their habitat environment. In this paper a modelling methodology to represent and analyse a context-aware multi agent-based system, which tends to be highly complex is proposed. CPN models are used to specify citizen’s preferences and affinities in front of an urban contextual change, while MAS is used to evaluate the social dynamics by translating the CPN semantic rules into agent’s rules in NetLogo.

Validation of Agent-Based Urban Policy Models by Means of State Space Analysis

Simulation trust is a critical issue to foster e-participation in the new e-governance framework in which it is expected to increase citizens participation in the design or urban policies. In social science, no firm conclusions have been reached on the appropriate way to verify or validate Agent Based Models, due to several aspects, such as agent capacity to take decisions autonomously. This paper considers some of the difficulties in establishing verification and validation of agent based models, and proposes the use of coloured petri net formalism to specify agent behaviour in order to check if the model looks logical and the model behaves logical. Model plausibility is used to express the conformity of the model with a priori knowledge about the process. The proposed methodology has been applied in the European Future Policy Modelling project (www.fupol.eu) to create trust and increase the credibility of the agent based models developed to foster e-participation in the design of urban policies by means of simulation techniques.