Enhancing symbolic system synthesis through ASPmT with partial assignment evaluation

Neubauer, Kai; Wanko, Philipp; Schaub, Torsten; Haubelt, Christian

doi:10.23919/date.2017.7927005

Cited by 14 publications

(9 citation statements)

References 12 publications

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“…We then presented AMT encodings that capture all these aspects. The system synthesis problem has been previously tackled with ASP [17][18][19][20][21]. This application is inherently hybrid as routing and conflict detection and resolution of messages are combinatorial in nature and require reachability, which can be easily handled with plain ASP.…”

Section: Discussionmentioning

confidence: 99%

Evolutionary System Design with Answer Set Programming

et al. 2023

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We address the problem of evolutionary system design (ESD) by means of answer set programming modulo difference constraints (AMT). The goal of this design approach is to synthesize new product variants or generations from existing products. We start by formalizing the underlying system synthesis problem and design space exploration process, which consists of finding the Pareto front with respect to latency, cost, energy, and similarity measures between the two designs. We then present AMT-based encodings to capture all of these aspects. The idea is to use plain ASP for conflict detection and resolution and for routing and to use difference constraints for scheduling. Moreover, we propose a new approach for expressing the similarity that we use at three alternative levels of AMT-based design space exploration, namely, at the strategic, heuristic, and objective levels, which is performed to guide the exploration towards designs of high interest. Last but not least, we systematically evaluate the emerging techniques empirically and identify the most promising AMT techniques.

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Section: Discussionmentioning

confidence: 99%

Evolutionary System Design with Answer Set Programming

et al. 2023

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“…Action durations and intervals were previously considered in ASP by Son et al (2004). Notably, we checked that clingo requires less than 1 GB of RAM to represent durations and makespan of a full production cycle at the car factory of Mercedes-Benz Ludwigsfelde GmbH, while extensions by difference logic (Neubauer et al 2017) or integer variables (Banbara et al 2017) may possibly handle even greater time intervals in a compact way.…”

Section: Discussionmentioning

confidence: 99%

Routing Driverless Transport Vehicles in Car Assembly with Answer Set Programming

Gebser¹,

Obermeier²,

Schaub³

et al. 2018

Theory and Practice of Logic Programming

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Automated storage and retrieval systems are principal components of modern production and warehouse facilities. In particular, automated guided vehicles nowadays substitute human-operated pallet trucks in transporting production materials between storage locations and assembly stations. While low-level control systems take care of navigating such driverless vehicles along programmed routes and avoid collisions even under unforeseen circumstances, in the common case of multiple vehicles sharing the same operation area, the problem remains how to set up routes such that a collection of transport tasks is accomplished most effectively. We address this prevalent problem in the context of car assembly at Mercedes-Benz Ludwigsfelde GmbH, a large-scale producer of commercial vehicles, where routes for automated guided vehicles used in the production process have traditionally been hand-coded by human engineers. Such ad-hoc methods may suffice as long as a running production process remains in place, while any change in the factory layout or production targets necessitates tedious manual reconfiguration, not to mention the missing portability between different production plants. Unlike this, we propose a declarative approach based on Answer Set Programming to optimize the routes taken by automated guided vehicles for accomplishing transport tasks. The advantages include a transparent and executable problem formalization, provable optimality of routes relative to objective criteria, as well as elaboration tolerance towards particular factory layouts and production targets. Moreover, we demonstrate that our approach is efficient enough to deal with the transport tasks evolving in realistic production processes at the car factory of Mercedes-Benz Ludwigsfelde GmbH.

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“…In this section we present a succinct summary of the integral parts of our SMT-based system synthesis implementation. We start with introducing state-of-the-art classical SMTbased system synthesis, which is similar to work presented in [5][6][7]9,10]. Then, we sketch the obstacles that motivated us to integrate our extensions in order to realize our proposed coordinated synthesis approach.…”

Section: Coordinated Smt-based Synthesis Approach: Motivation and Det...mentioning

confidence: 99%

Improving Symbolic System-Level Synthesis by Solver Coordination and Domain-Specific Heuristics

Haubelt

Rausch

2022

Electronics

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Deciding binding, routing, and scheduling within system synthesis for hard real-time systems can be a challenging task. Symbolic methods leveraging results from the area of satisfiability modulo theories (SMT) solving have shown to be scalable methods for this by splitting the work between a logic solver for routing and binding, and a background theory solver performing schedulability analysis. For these methods, in order to prune the search space of infeasible implementations efficiently, a feedback by the background theory is required. It can be observed that previous approaches might fail here as feedback cannot be derived within a reasonable amount of time. We propose a coordinated synthesis approach that overcomes this issue. Here, we leverage an answer set solver as logic solver that is enhanced with a scheduling-aware binding and routing refinement. Based on the answer set solver’s decisions for binding and routing, a background theory solver then computes time-triggered schedules to resolve resource access conflicts. If no feasible schedule exists, a feedback to the answer set solver can be derived within reasonable time. Our experiments synthesizing massively parallel hardware architectures show that our approach increases the applicability of symbolic synthesis considerably. While more than half of the investigated instances in our experiments cannot be solved in the non-coordinated approach already at small 2-dimensional 3×3 tiled mesh hardware architectures with 60% average computational utilization per tile, the coordinated synthesis approach scales up to 5×5 architectures with average utilization of 70% per tile (2.8× the hardware architecture size than before). Furthermore, we increase the scalability and the robustness of our approach by encoding our domain-knowledge within domain-specific heuristics in our designated answer set solver. Within our experiments, we observe that the domain-specific heuristics enable us to scale up to 6×6 architectures with 70% average utilization per tile.

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Enhancing symbolic system synthesis through ASPmT with partial assignment evaluation

Cited by 14 publications

References 12 publications

Evolutionary System Design with Answer Set Programming

Evolutionary System Design with Answer Set Programming

Routing Driverless Transport Vehicles in Car Assembly with Answer Set Programming

Improving Symbolic System-Level Synthesis by Solver Coordination and Domain-Specific Heuristics

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