Optimal Scheduling Using Branch and Bound with SPIN 4.0

The use of model checkers to solve discrete optimisation problems is appealing. A model checker can first be used to verify that the model of the problem is correct. Subsequently, the same model can be used to find an optimal solution for the problem. This paper describes how to apply the new PROMELA primitives of SPIN 4.0 to search effectively for the optimal solution. We show how Branch-and-Bound techniques can be added to the LTL property that is used to find the solution. The LTL property is dynamically changed during the verification. We also show how the syntactical reordering of statements and/or processes in the PROMELA model can improve the search even further. The techniques are illustrated using two running examples: the Travelling Salesman Problem and a job-shop scheduling problem

Optimal Scheduling Using Branch and Bound with SPIN 4.0

The use of model checkers to solve discrete optimisation problems is appealing. A model checker can first be used to verify that the model of the problem is correct. Subsequently, the same model can be used to find an optimal solution for the problem. This paper describes how the new Promela primitives of Spin 4.0 can be applied to search e#ectively for the optimal solution. We show how Branch-and-Bound techniques can be added to the LTL property that is used to find the solution. The LTL property is dynamically changed during the verification

Scheduling Optimisations for SPIN to Minimise Buffer Requirements in Synchronous Data Flow

Synchronous Data flow (SDF) graphs have a simple and elegant semantics (essentially linear algebra) which makes SDF graphs eminently suitable as a vehicle for studying scheduling optimisations. We extend related work on using SPIN to experiment with scheduling optimisations aimed at minimising buffer requirements.We show that for a benchmark of commonly used case studies the performance of our SPIN based scheduler is comparable to that of state of the art research tools. The key to success is using the semantics of SDF to prove when using (even unsound and/or incomplete) optimisations are justified. The main benefit of our approach lies in gaining deep insight in the optimisations at relatively low cost

Advanced SPIN Tutorial

Spin [9] is a model checker for the verification of distributed systems software. The tool is freely distributed, and often described as one of the most widely used verification systems. The Advanced Spin Tutorial is a sequel to [7] and is targeted towards intermediate to advanced Spin users

Taming Numbers and Durations in the Model Checking Integrated Planning System

The Model Checking Integrated Planning System (MIPS) is a temporal least commitment heuristic search planner based on a flexible object-oriented workbench architecture. Its design clearly separates explicit and symbolic directed exploration algorithms from the set of on-line and off-line computed estimates and associated data structures. MIPS has shown distinguished performance in the last two international planning competitions. In the last event the description language was extended from pure propositional planning to include numerical state variables, action durations, and plan quality objective functions. Plans were no longer sequences of actions but time-stamped schedules. As a participant of the fully automated track of the competition, MIPS has proven to be a general system; in each track and every benchmark domain it efficiently computed plans of remarkable quality. This article introduces and analyzes the most important algorithmic novelties that were necessary to tackle the new layers of expressiveness in the benchmark problems and to achieve a high level of performance. The extensions include critical path analysis of sequentially generated plans to generate corresponding optimal parallel plans. The linear time algorithm to compute the parallel plan bypasses known NP hardness results for partial ordering by scheduling plans with respect to the set of actions and the imposed precedence relations. The efficiency of this algorithm also allows us to improve the exploration guidance: for each encountered planning state the corresponding approximate sequential plan is scheduled. One major strength of MIPS is its static analysis phase that grounds and simplifies parameterized predicates, functions and operators, that infers knowledge to minimize the state description length, and that detects domain object symmetries. The latter aspect is analyzed in detail. MIPS has been developed to serve as a complete and optimal state space planner, with admissible estimates, exploration engines and branching cuts. In the competition version, however, certain performance compromises had to be made, including floating point arithmetic, weighted heuristic search exploration according to an inadmissible estimate and parameterized optimization

Optimal trajectory generation for Petri nets

Recently, the increasing complexity of IT systems requires the early verification and validation of the system design in order to avoid the costly redesign. Furthermore, the efficiency of system operation can be improved by solving system optimization problems (like resource allocation and scheduling problems). Such combined optimization and validation, verification problems can be typically expressed as reachability problems with quantitative or qualitative measurements. The current paper proposes a solution to compute the optimal trajectories for Petri net-based reachability problems with cost parameters. This is an improved variant of the basic integrated verification and optimization method introduced in [11] combining the efficiency of Process Network Synthesis optimization algorithms with the modeling power of Petri nets

Efficient scheduling of batch processes in continuous processing lines

This thesis focuses mainly on the development of efficient formulations for scheduling in industrial environments. Likewise, decisions over the processes more related to advanced process control or production planning are included in the scheduling; in this way, the schedule obtained will be more efficient than it would be if the additional restrictions were not considered. The formulations have to emphasize obtaining online implementations, as they are planned to be used in real plants. The most common scheduling problems handled in the industrial environments are: the assignment of tasks to units, the distribution of production among parallel units and the distribution of shared resources among concurrent processes. Most advances in this work are the result of a collaborative work.Departamento de Ingeniería de Sistemas y AutomáticaDoctorado en Ingeniería Industria

Symmetry reduction and heuristic search for error detection in model checking

The state explosion problem is the main limitation of model checking. Symmetries in the system being verified can be exploited in order to avoid this problem by defining an equivalence (symmetry) relation on the states of the system, which induces a semantically equivalent quotient system of smaller size. On the other hand, heuristic search algorithms can be applied to improve the bug finding capabilities of model checking. Such algorithms use heuristic functions to guide the exploration. Bestfirst is used for accelerating the search, while A* guarantees optimal error trails if combined with admissible estimates. We analyze some aspects of combining both approaches, concentrating on the problem of finding the optimal path to the equivalence class of a given error state. Experimental results evaluate our approach