Max-Plus-Linear Research Articles

SMT-Based Reachability Analysis of High Dimensional Interval Max-Plus Linear Systems

This paper discusses the reachability analysis (RA) of Interval Max-Plus Linear (IMPL) systems, a subclass of continuous-space, discrete-event systems defined over the max-plus algebra. Unlike standard Max-Plus Linear (MPL) systems, where the transition matrix is fixed at each discrete step, IMPL systems allow for uncertainty on state matrices. Given an initial and a target set, we develop algorithms to verify the existence of IMPL system trajectories that, starting from the initial set, eventually reach the target set. We show that RA can be solved by encoding the IMPL system, as well as initial and target sets, into linear real arithmetic expressions, and then checking the satisfaction of a resulting logical formula via a satisfiability modulo theory (SMT) solver. The performance and scalability of the developed SMT-based algorithms are shown to drastically outperform state-of-the-art RA algorithms applied to IMPL systems, which promises to usher their use in practical, industrial-sized IMPL models.

APPLICATION OF SYSTEM MAX-PLUS LINEAR EQUATIONS ON SERIAL MANUFACTURING MACHINE WITH STORAGE UNIT

The set together with the operation maximum (max) denoted as and addition (+) denoted as is called max-plus algebra. Max-plus algebra may be used to apply algebraically a few programs of Discrete Event Systems (DES), certainly one of the examples in the production system. In this study, the application of max-plus algebra in a serial manufacturing machine with a storage unit is discussed. The results of this are the generalization system max-plus-linear equations on a production system that is, in addition, noted the max-plus-linear time-invariant system. From the max-plus-linear time-invariant system, it can be obtained the equation which is then used to determine the beginning time of a production system so the manufacturing machine work periodically. The eigenvector and eigenvalue of the matrix are then used to find the beginning time and the period time of the manufacturing machine. Furthermore, the time when the product leaves the manufacturing machine with the time while the raw material enters the manufacturing machine is given and vice versa are obtained from the max-plus-linear time-invariant system that is can be formed in the equation .

MODELING PREDICTIVE TRACKING CONTROL FOR MAX-PLUS LINEAR SYSTEMS IN MANUFACTURING

Discrete event systems, also known as DES, are class of system that can be applied to systems having an event that occurred instantaneously and may change the state. It can also be said that a discrete event system occurs under certain conditions for a certain period because of the network that describes the process flow or sequence of events. Discrete event systems belong to class of nonlinear systems in classical algebra. Based on this situation, it is necessary to do some treatments, one of which is linearization process. In the other hand, a Max-Plus Linear system is known as a system that produces linear models. This system is a development of a discrete event system that contains synchronization when it is modeled in Max-Plus Algebra. This paper discusses the production system model in manufacturing industries where the model pays the attention into the process flow or sequence of events at each time step. In particular, Model Predictive Control (MPC) is a popular control design method used in many fields including manufacturing systems. MPC for Max-Plus-Linear Systems is used here as the approach that can be used to model the optimal input and output sequences of discrete event systems. The main advantage of MPC is its ability to provide certain constraints on the input and output control signals. While deciding the optimal control value, a cost criterion is minimized by determining the optimal time in the production system that modeled as a Max-Plus Linear (MPL) system. A numerical experiment is performed in the end of this paper for tracking control purposes of a production system. The results were good that is the controlled system showed a good performance.

An Algorithm to Compute the Inverse Image of a Point With Respect to a Nondeterministic Max-Plus Linear System

Max-plus linear (MPL) systems are often described by a transition function, which models the state evolution of the system, and a measurement function, which binds the measures with the system states. Methods for computing the inverse image of a point w.r.t. the measurement function are particularly interesting in applications where it is desirable to obtain information about the system states based on the output observations. The inverse image of a set w.r.t. a nondeterministic MPL system, called uncertain MPL (uMPL) system, can be computed by using the difference-bound matrices (DBM) approach. In this article, we aim to use an interval analysis to propose a method to compute the inverse image of a point w.r.t. an uMPL system. The algorithm proposed has a lower worst-case complexity compared with the DBM approach as previously proposed in the literature.

Symbolic Reachability Analysis of High Dimensional Max-Plus Linear Systems

Abstract This work discusses the reachability analysis (RA) of Max-Plus Linear (MPL) systems, a class of continuous-space, discrete-event models defined over the max-plus algebra. Given the initial and target sets, we develop algorithms to verify whether there exist trajectories of the MPL system that, starting from the initial set, eventually reach the target set. We show that RA can be solved symbolically by encoding the MPL system, as well as initial and target sets into difference logic, and then checking the satisfaction of the resulting logical formula via an off-the-shelf satisfiability modulo theories (SMT) solver. The performance and scalability of the developed SMT-based algorithms are shown to clearly outperform state-of-the-art RA algorithms for MPL systems, newly allowing to investigate RA of high-dimensional MPL systems: the verification of models with more than 100 continuous variables shows the applicability of these techniques to MPL systems of industrial relevance.

Conditional reachability of uncertain Max Plus Linear systems

The reachability analysis problem of Max Plus Linear (MPL) systems has been properly solved using the Difference-Bound Matrices approach. In this work, the same approach is considered in order to solve the reachability analysis problem of MPL systems subjected to bounded noise, disturbances and/or modeling errors, called uncertain MPL (uMPL) systems. Moreover, using the results on the reachability analysis of uMPL systems, we solve the conditional reachability problem, herein defined as the support calculation of the probability density function involved in the stochastic filtering problem.

Object Oriented Design of Software Tool for Finite Abstractions of Max-Plus-Linear Systems using Unified Modeling Language

Max-Plus-Linear (MPL) systems are a class of discrete-event systems with a continuous state space characterizing the timing of the underlying sequential discrete events. There is a formal approach to analyze these systems based on finite abstractions. The abstraction algorithms have been in MATLAB using list data structure and in JAVA using tree data structure. The MATLAB implementation requires long computational time, whereas the JAVA one requires larger memory allocation. In this work, we discuss an object oriented design in C++ using tree data structure without recursive functions in the hope of improving the results obtained by the two previous implementations.

Reduction and Analysis of a Max-Plus Linear System to a Constraint Satisfaction Problem for Mixed Integer Programming

This research develops a solution method for project scheduling represented by a max-plus-linear (MPL) form. Max-plus-linear representation is an approach to model and analyze a class of discrete-event systems, in which the behavior of a target system is represented by linear equations in max-plus algebra. Several types of MPL equations can be reduced to a constraint satisfaction problem (CSP) for mixed integer programming. The resulting formulation is flexible and easy-to-use for project scheduling; for example, we can obtain the earliest output times, latest task-starting times, and latest input times using an MPL form. We also develop a key method for identifying critical tasks under the framework of CSP. The developed methods are validated through a numerical example.

Forward-compatible framework with critical-chain project management using a max-plus linear representation

Focusing on projects with uncertain task-duration times under limited resources, we develop a scheduling framework using a max-plus linear (MPL) representation. The base methodology is referred to as critical-chain project management (CCPM), designed to achieve a short lead time and observe the estimated due date. Our recent achievement called CCPM-MPL is an approach to handle the CCPM framework using an MPL representation; therein, no method for resolving resource contention is provided. We thus improve the existing CCPM-MPL framework for which it becomes compliant and forward compatible with the original CCPM. The forward compatibility yields additional benefits; it is able to list and compare all potential schedules with the same processing sequence. It can also handle multiple-input and/or multiple-output projects in a unified fashion. The former would be useful in instances when we are allowed to deliver multiple products separately, the latter when one or more resource is unavailable until a certain time.

VeriSiMPL 2: An open-source software for the verification of max-plus-linear systems

This work presents a technique to generate finite abstractions of autonomous Max-Plus-Linear (MPL) systems, a class of discrete-event systems employed to characterize the dynamics of the timing related to the synchronization of successive events. Abstractions of MPL systems are derived as finite-state transition systems. A transition system is obtained first by partitioning the state space of the MPL system into finitely many regions and then by associating a unique state of the transition system to each partitioning region. Relations among the states of the transition system are then set up based on the underlying dynamical transitions between the corresponding partitioning regions of the MPL state space. In order to establish formal equivalences, the obtained finite abstractions are proven either to simulate or to bisimulate the original MPL system. The approach enables the study of general properties of the original MPL system formalized as logical specifications, by verifying them over the finite abstraction via model checking. The article presents a new, extended and improved implementation of a software tool (available online) for the discussed formal abstraction of MPL systems, and is tested on a numerical benchmark against a previous version.

Computational techniques for reachability analysis of Max-Plus-Linear systems

This work discusses a computational approach to reachability analysis of Max-Plus-Linear (MPL) systems, a class of discrete-event systems widely used in synchronization and scheduling applications. Given a set of initial states, we characterize and compute its “reach tube,” namely the collection of set of reachable states (regarded step-wise as “reach sets”). By an alternative characterization of the MPL dynamics, we show that the exact computation of the reach sets can be performed quickly and compactly by manipulations of difference-bound matrices, and further derive worst-case bounds on the complexity of these operations. The approach is also extended to backward reachability analysis. The concepts and results are elucidated by a running example, and we further illustrate the performance of the approach by a numerical benchmark: the technique comfortably handles twenty-dimensional MPL systems (i.e. with twenty continuous state variables), and as such it outperforms the state-of-the-art alternative approaches in the literature.

Backward Reachability of Autonomous Max-Plus-Linear Systems

This work discusses the backward reachability of autonomous Max-Plus-Linear (MPL) systems, a class of continuous-space discrete-event models that are relevant for applications dealing with synchronization and scheduling. Given an MPL system and a continuous set of final states, we characterize and compute its “backward reach tube” and “backward reach sets, ” namely the set of states that can reach the final set within a given event interval or at a fixed event step, respectively. We show that, in both cases, the computation can be done exactly via manipulations of difference-bound matrices. Furthermore, we illustrate the application of the backward reachability computations over safety and transient analysis of MPL systems.

Finite Abstractions of Max-Plus-Linear Systems

This work puts forward a novel technique to generate finite abstractions of autonomous and nonautonomous Max-Plus-Linear (MPL) models, a class of discrete-event systems used to characterize the dynamics of the timing related to successive events that synchronize autonomously. Nonautonomous versions of MPL models embed within their dynamics nondeterminism, namely a signal choice that is usually regarded as an exogenous control or schedule. In this paper, abstractions of MPL models are characterized as finite-state Labeled Transition Systems (LTS). LTS are obtained first by partitioning the state space (and, for the nonautonomous model, by covering the input space) of the MPL model and by associating states of the LTS to the introduced partitions, then by defining relations among the states of the LTS based on dynamical transitions between the corresponding partitions of the MPL state space, and finally by labeling the LTS edges according to the one-step timing properties of the events of the original MPL model. In order to establish formal equivalences, the finite abstractions are proven to either simulate or to bisimulate the original MPL model. This approach enables the study of general properties of the original MPL model by verifying (via model checking) equivalent logical specifications over the finite LTS abstraction. The computational aspects related to the abstraction procedure are thoroughly discussed and its performance is tested on a numerical benchmark.

Buffer Management Method for Multiple Projects in the CCPM-MPL Representation

This research proposes a framework of buffer management for multi-project systems in the critical chain project management (CCPM) method, expressed in the form of max-plus linear (MPL) representation. Since time buffers are inserted in the projects for absorbing uncertainties in task durations and protecting the completion times, the proposed method provides a procedure for frequently surveying the rates of consumed buffers and the rate of elapsed times. Their relation expresses the performance of the projects which is plotted on a chart through the completed processes. The chart presents the current performance of the projects and their interaction, which alerts managers to make necessary decisions at the right time for managing each project and the entire multi-project system. The proposed framework can analyze the complex system readily, and it enables managers to make an effective decision on scheduling. The effectiveness of the framework is demonstrated through a numerical example.

Critical Chain Project Management Based on a Max-Plus Linear Representation for Determining Time Buffers in Multiple Projects

We propose a framework for describing the Critical Chain Project Management (CCPM) method based on a Max-Plus Linear (MPL) representation for multiple projects. The framework takes into account time buffers in both a single and multi-project environments which play a role for controlling undesirable state change and protecting the completion time for the entire system. The appropriate position and size of these buffers are determined for a large scale multi-project system. Furthermore, the MPL system with the CCPM method applied is redefined to easily comprehend the structure of the system. Finally, we confirm the proposed framework through a numerical example.

Resolution of Time and Worker Conflicts for a Single Project in a Max-Plus Linear Representation

This research develops a framework for resolving time and worker conflicts in the Critical Chain Project Management (CCPM) method, expressed in the form of a Max-Plus Linear (MPL) system. Our previous work proposed a method for resolving time conflicts. However, in practical cases, both time and worker conflicts may occur. Hence, we propose a method for resolving both time and worker conflicts for a single project. We first consider how to detect a resource conflict. Then, we define an adjacency matrix to resolve the detected conflicts. Using the proposed method, we confirm that the resource conflict can be resolved through a numerical example.

Resolution of resource conflict between the different two projects in MPL-CCPM representation

Max-Plus-Linear (MPL) system is known as a solution for scheduling problems of a class of discrete event systems. Typical systems include: manufacturing system and project management, etc. In such ...

Efficient Calculation of the Transition Matrix in a Max-Plus Linear State-Space Representation

This research considers an efficient method for calculating the transition matrix in an MPL (Max-Plus Linear) state-space representation. This matrix can be generated by applying the Kleene star operator to an adjacency matrix. The proposed method, based on the idea of a topological sort in graph theory and block splitting, is able to calculate the transition matrix efficiently.

Stabilization of max-plus-linear systems using model predictive control: The unconstrained case

Max-plus-linear (MPL) systems are a class of event-driven nonlinear dynamic systems that can be described by models that are “linear” in the max-plus algebra. In this paper we derive a solution to a finite-horizon model predictive control (MPC) problem for MPL systems where the cost is designed to provide a trade-off between minimizing the due date error and a just-in-time production. In general, MPC can deal with complex input and states constraints. However, in this paper we assume that these are not present and it is only required that the input should be a nondecreasing sequence, i.e. we consider the “unconstrained” case. Despite the fact that the controlled system is nonlinear, by employing recent results in max-plus theory we are able to provide sufficient conditions such that the MPC controller is determined analytically and moreover the stability in terms of Lyapunov and in terms of boundedness of the closed-loop system is guaranteed a priori.

Consideration of Capacity and Order Constraints for Event-Varying MPL Systems

This letter extends the existent MPL (Max-Plus Linear) state-space representation and proposes a new form that can account for both capacity and order constraints. It is often essential to consider these factors when applying the MPL approach to scheduling problems for production or transportation systems. The derived form is a type of augmented state-representation and can contribute to obtaining the earliest start and completion times for processes in installed facilities.