Non-blocking supervisors synthesis for a class of discrete event systems based on two-stage deadlock control

Based on elementary siphons of Petri nets and the mixed integer programming approach, an improved deadlock prevention policy is developed for S/sup 3/PR. Siphons in such a plant Petri net model are divided into elementary and dependent ones. Our policy consists of two stages: siphon control and control-induced siphon control. At first stage, a monitor (control place) is added for each elementary siphon such that it is invariant-controlled. Due to the addition of monitors to plant model, control-induced siphons are possibly generated in the augmented S/sup 3/PR, which is an RCN-merged net. The second stage sees that monitors are added to make always marked control-induced siphons in the resultant RCN-merged net without generating new control-induced siphons. Compared with our previous work, the deadlock prevention policy developed in this paper can lead to a structurally simple liveness-enforcing Petri net supervisor by adding only a small number of monitors and arcs. An FMS example is utilized to illustrate the proposed methods.

Liveness-enforcing supervisors (LESs) guarantee deadlock-free operations in resource allocation systems (RASs). Given the growing emphasis on higher resource utilization and operational flexibility, it is greatly desirable to obtain the optimal LES that can provide the maximum behavioral latitude. In general, however, computation of the maximally permissive LES is computationally intractable and, accordingly, the class of algebraic LESs has been proposed in the literature as a viable suboptimal alternative for various RAS classes. The objective of this work is to further enhance the permissiveness of algebraic LESs by taking advantage of the routing flexibility inherent in contemporary RASs. Specifically, we consider a class of algebraic LES that allows supervisor parameterizations based on the system routing flexibility, and propose a method to effectively mix the algebraic LESs obtained from the policy instantiation through a set of different parameter values. The resulting policy mixture, to be called dynamic algebraic LES, provides increased permissiveness as it allows flexible online switching among different resource reservation schemes, corresponding to different process routings. The proposed method for constructing the dynamic algebraic LES is presented in the context of the class of conjunctive/disjunctive RASs, which subsumes the major RAS classes currently studied in the literature.

Petri nets are an effective way to model, analyze, and control deadlocks in automated manufacturing systems (AMS). There are three important criteria in designing and evaluating a liveness-enforcing supervisor for a system to be controlled: behavioral permissiveness, structural complexity, and computational complexity. A maximally permissive supervisor can lead to high utilization of system resources. A supervisor with a simple structure can decrease the hardware and software costs. As for the computational complexity, means that a deadlock control policy can be applied to large systems. The objective of this paper is to design liveness-enforcing supervisors for different flexible manufacturing systems, simulate the controlled systems, and estimate the utilization of resources and throughput of the system. The siphon control methods (Strict Minimal Siphons and Elementary Siphons) are used to solve the deadlock control problems for a number of AMSs with different sizes. Moreover, the paper aims to evaluate the performance of selected methods such as utilization of resources, throughput, and the number of monitors, arcs, and states. Finally, the computational results indicate that the elementary siphons based policy provides better structural complexity and computational complexity than the strict minimal siphons based policy. However, strict minimal siphons based policy leads to better behavioral permissiveness than elementary siphons methods.

During the operation of a complex machine or device, it is necessary to perform complete or partial disassembly of the product and its individual components and assemblies. Disassembly operations are required for repair, maintenance and disposal of technical system components at the end of their service life. Modern technical systems can consist of several thousand (or more) parts and components. Therefore, it is necessary to use modern computing and design automation tools to plan disassembly processes and operations. The sequence of disassembly and the content of disassembly operations largely depend on the mechanical structure of the product. To model the mechanical structures of complex products in CAD-systems, various graph and network models are mainly used. The paper gives an overview of the most popular models of this type. The main carrier of information about the mechanical structure of a product is the so-called liaison graph. The review considers design procedures for synthesizing disassembly processes using the liaison graph. Procedures of expert ordering and procedures based on cuts in the liaison graph.

Automated manufacturing systems (AMSs) are developing rapidly with increasingly sophisticated operations and complex topologies. In this paper, we propose a new kind of AMS structure, namely, AESMs, with processes expressed by flexible routes and embedded by marked graph blocks. Flexible routes and assembly operations are combined organically in this model, making it structurally complex and applicably adaptable. Deadlock resolution in AMSs is a fundamental and prerequisite issue. Conventional approach is based on monolithic methodologies by means of siphons, i.e., a special structural object closely related to deadlocks. Analysis shows that siphon-based mechanism is of limited applicability to control AESMs. On the contrary, we utilize a distributed approach in accordance with the philosophy of model predictive control techniques, which can create a trajectory dynamically leading the entire system to its desired destination. In our strategy, whether or not concerned tokens can reach critical places or critical place unities determines the feasibility of each step's execution. Control strategy is applied to processes locally such that they can concurrently proceed at the same pace. Global goals become attainable through the local observation, control, and execution upon local processes without knowing external and extra information.

In the context of automated manufacturing systems (AMS), Petri nets are widely adopted to solve the modeling, analysis, and control problems. So far, nearly all well-known Petri net approaches study AMS with either flexible routes or assembly operations, whereas few work investigates their combination. In this paper, we propose a novel class of nets, which can well deal with both features. We also derive a supervisory controller for on-line ratio enforcement among all processes. Using structural analysis, we show that liveness of such systems can be attributed to the absence of undermarked siphons. We also reveal the design separability between ratio-enforcing and liveness-enforcing supervisors.

An optimization procedure is described that can serve to identify attractive regionalization plans for large wastewater treatment and collection systems. Potential expansion of facilities in Western Suffolk County, Long Island, New York is considered. A mixed integer programming approach is utilized. Each system element cost, taken as a function of wastewater flow, is represented by a linear variable cost plus a fixed cost. The objective is to minimize total cost while ensuring that all wastewater flow generated is treated. Political and administrative feasibility and the location of effluent discharge constrain the model. The Long Island problem is too large to be solved with a standard formulation of wastewater network as a mixed integer programming problem. To improve computational efficiency, additional constraints are introduced on the minimum flow in each pipe and on the number of pipes leaving each node. Network configurations obtained for Western Suffolk County show that limiting development plans to 201 regions is not cost effective. Regional solutions indicate a general trade‐off between lower costs for coastal discharge and increased groundwater recharge.

Subset selection by Mallows’ [formula omitted]: A mixed integer programming approach

The sugarcane transport system is very complex and uses a daily schedule, consisting of a set of locomotives runs, to satisfy the requirements of the mill and harvesters. The total cost of sugarcane transport operations is very high; over 35% of the total cost of sugarcane production in Australia is incurred in cane transport. Producing efficient schedules for sugarcane transport can reduce the cost and limit the negative effects that this system can have on the raw sugar production system. In this paper, the sugarcane rail operations are formulated as a blocking job shop scheduling problem. A mixed integer programming approach is used to formulate the shop job scheduling problem. Mixed integer programming and constraint programming search techniques are integrated for solving the problem. A case study is solved to test the approach.

Appointment schedules for outpatient clinics have great influence on efficiency and timely access to health care services. The number of new patients per week fluctuates, and capacity at the clinic varies because physicians have other obligations. However, most outpatient clinics use static appointment schedules, which reserve capacity for each patient type. In this paper, we aim to optimise appointment scheduling with respect to access time, taking fluctuating patient arrivals and unavailabilities of physicians into account. To this end, we formulate a stochastic mixed integer programming problem, and approximate its solution invoking two different approaches: (1) a mixed integer programming approach that results in a static appointment schedule, and (2) Markov decision theory, which results in a dynamic scheduling strategy. We apply the methodologies to a case study of the surgical outpatient clinic of the Jeroen Bosch Hospital. We evaluate the effectiveness and limitations of both approaches by discrete event simulation; it appears that allocating only 2% of the capacity flexibly already increases the performance of the clinic significantly.

Selecting Optimal Mix of Machines for Various Type of Rice Farming in Korea : A Mixed Integer Programming Approach

We consider complete partitioning of bandwidth among multiple services. When class bandwidth is an integer multiple of the next lower class and total bandwidth is an integer multiple of the largest class bandwidth, we develop a recursive algorithm that determines the optimal complete partitioning policy with a significantly lower complexity than that of known dynamic programming or mixed integer programming approaches.

A novelty detection machine and its application to bank failure prediction

We consider the necessary redistribution of bicycles in public bicycle sharing systems in order to avoid rental stations to run empty or entirely full. For this purpose we propose a general Variable Neighborhood Search (VNS) with an embedded Variable Neighborhood Descent (VND) that exploits a series of neighborhood structures. While this metaheuristic generates candidate routes for vehicles to visit unbalanced rental stations, the numbers of bikes to be loaded or unloaded at each stop are efficiently derived by one of three alternative methods based on a greedy heuristic, a maximum flow calculation, and linear programming, respectively. Tests are performed on instances derived from real-world data and indicate that the VNS based on a greedy heuristic represents the best compromise for practice. In general the VNS yields good solutions and scales much better to larger instances than two mixed integer programming approaches.

Dynamic hoist scheduling problem with multi-capacity reentrant machines: A mixed integer programming approach