Handbook of Metaheuristics

Schulze, Sabine

doi:10.1007/978-3-319-91086-4

Cited by 127 publications

(4 citation statements)

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“…Such challenges, where a large solution space exists and several constraints have to be considered, are subject to optimization questions and can be boiled down to a search problem in the solution space. Search-based software engineering [52][53][54] is a well-established software engineering field that applies meta-heuristic algorithms [39] to automatically solve such search problems. Similar to our previous work on automatically completing underspecified scenario models [110], the problem of finding real-time-feasible platform-specific MSD specifications could be encoded as input to a metaheuristic algorithm that has to incorporate the timing analysis results.…”

Section: Discussionmentioning

confidence: 99%

Early timing analysis based on scenario requirements and platform models

2022

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Distributed, software-intensive systems (e.g., in the automotive sector) must fulfill communication requirements under hard real-time constraints. The requirements have to be documented and validated carefully using a systematic requirements engineering (RE) approach, for example, by applying scenario-based requirements notations. The resources of the execution platforms and their properties (e.g., CPU frequency or bus throughput) induce effects on the timing behavior, which may lead to violations of the real-time requirements. Nowadays, the platform properties and their induced timing effects are verified against the real-time requirements by means of timing analysis techniques mostly implemented in commercial-off-the-shelf tools. However, such timing analyses are conducted in late development phases since they rely on artifacts produced during these phases (e.g., the platform-specific code). In order to enable early timing analyses already during RE, we extend a scenario-based requirements notation with allocation means to platform models and define operational semantics for the purpose of simulation-based, platform-aware timing analyses. We illustrate and evaluate the approach with an automotive software-intensive system.

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Section: Discussionmentioning

confidence: 99%

Early timing analysis based on scenario requirements and platform models

2022

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“…In this work, we use variable neighborhood search (VNS) to solve this integrated problem. Variable neighborhood search is a relatively new metaheuristic (proposed by Mladenović & Hansen (1997)), and its basic idea is a systematic change of neighborhood both within a descent phase to find a local optimum and in a perturbation phase to get out of the corresponding valley (according to Gendreau & Potvin (2010)).…”

Section: Variable Neighborhood Search Algorithm For Integrated Order ...mentioning

confidence: 99%

Formulating and solving integrated order batching and routing in multi-depot AGV-assisted mixed-shelves warehouses

Xie¹,

Li²,

Luttmann³

2021

Preprint

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Different retail and e-commerce companies are facing the challenge of assembling large numbers of time-critical picking orders that include both single-line and multi-line orders. To reduce unproductive picker working time as in traditional picker-to-parts warehousing systems, different solutions are proposed in the literature and in practice. For example, in a mixed-shelves storage policy, items of the same stock keeping unit are spread over several shelves in a warehouse; or automated guided vehicles (AGVs) are used to transport the picked items from the storage area to packing stations instead of human pickers. This is the first paper to combine both solutions, creating what we call AGV-assisted mixed-shelves picking systems. We model the new integrated order batching and routing problem in such systems as an extended multi-depot vehicle routing problem with both three-index and two-commodity network flow formulations. Due to the complexity of the integrated problem, we develop a novel variable neighborhood search algorithm to solve the integrated problem more efficiently. We test our methods with different sizes of instances, and conclude that the mixed-shelves storage policy is more suitable than the usual storage policy in AGV-assisted mixed-shelves systems for both single-line and multi-line orders (saving up to 67% on driving distances for AGVs). Our variable neighborhood search algorithm provides close-to-optimal solutions within an acceptable computational time.

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“…Because in such cases, since the failure probability of all components are at a low level and almost not so different from each other, their cost values stand out in determining the component to maintain. To prevent this situation, a tabu list inspired from the well known tabu search algorithm in meta-heuristics [33] is kept. After a component is maintained proactively or reactively, it is added to this list and it cannot be maintained proactively until its tabu duration expires.…”

Section: Tabu Proceduresmentioning

confidence: 99%

Evaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs

Özgür-Ünlüakın

Türkali

2021

Reliability Engineering & System Safety

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In complex systems with stochastically dependent components which are not observed directly, determining an effective maintenance policy is a difficult task. In this paper, a dynamic Bayesian network based maintenance decision framework is proposed to evaluate proactive maintenance policies for such systems. Two preventive and one predictive maintenance strategies from a cost perspective are designed for multicomponent dependable systems which aim to reduce maintenance cost while increasing system reliability at the same time. Tabu procedure is employed to avoid repetitive similar actions. The performances of the policies are compared with a reactive maintenance strategy and also with each other using different strategy parameters on a real life system confronted in thermal power plants for six different scenarios. The scenarios are designed considering different structures of system dependability and reactive cost. The results show that the threshold based maintenance which is the predictive strategy gives the minimum cost and maintenance number in almost all scenarios.

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Handbook of Metaheuristics

Cited by 127 publications

References 0 publications

Early timing analysis based on scenario requirements and platform models

Early timing analysis based on scenario requirements and platform models

Formulating and solving integrated order batching and routing in multi-depot AGV-assisted mixed-shelves warehouses

Evaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs

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