Anytime Column Search

Vadlamudi, Satya Gautam; Gaurav, Piyush; Aine, Sandip; Chakrabarti, P. P.

doi:10.1007/978-3-642-35101-3_22

Cited by 7 publications

(15 citation statements)

References 9 publications

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“…The search continues the iterative process until the solution converges to optimal, i.e., there are no more markings to be expanded. However, ABS is faced with re-expansion overhead since most of the markings in the previous iteration must be expanded in order to regenerate the pruned ones [24].…”

Section: Anytime Search Algorithmsmentioning

confidence: 99%

“…More recently, [24] propose anytime column search (ACS) which shares similar characteristics with ABS. Unlike ABS, ACS performs only admissible pruning in order to avoid the overhead of re-expanding markings.…”

Section: Anytime Search Algorithmsmentioning

confidence: 99%

“…Each iteration in the ACS creates a column in the state space viewed as a sliding window. Also, [24] discuss several ACS variants such as progressive, scaling, and adaptive. In this paper, we modified the adaptive variant such that the search can adjust dynamically to solution changes by varying the column width and propagating path cost improvement of duplicate markings.…”

Section: Anytime Search Algorithmsmentioning

confidence: 99%

“…For example, airport handling systems in which handling mobile resources should be ready at a certain location when the aircraft is in its parking position, subject to several time uncertainties. In this work, we adapt the anytime column search algorithm proposed by [24]. The search is combined with the condensed state space generation of TCPN models to schedule FMS.…”

Section: Introductionmentioning

confidence: 99%

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Anytime heuristic search for scheduling flexible manufacturing systems: a timed colored Petri net approach

Baruwa

Piera

2014

Int J Adv Manuf Technol

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Given the fluctuations in demand, diversity in products, production flexibility requirements, and tight customer due dates, obtaining optimal production schedules is considered a complex research problem. This can drastically affect the survival of some manufacturing companies in today's fiercely competitive global market. In a very demanding decision-making environment, scheduling problems are dealt with in a short-term horizon, in which computation time is a critical factor. Producing optimal solutions is practically impossible given the time limitations and the nondeterministic polynomial (NP)-hard nature of scheduling problems. This paper presents an anytime-heuristic search approach based on a simulation-optimization framework that combines evaluation methods (simulation) and search methods (optimization) through the reachability analysis (or state space) of timed colored Petri net models to schedule flexible manufacturing systems (FMS). The anytime search algorithm is capable of finding a first suboptimal solution very quickly and continuously improves the solution quality over time. If given enough computation time, the algorithm eventually converges to an optimal solution. The proposed approach is aimed at obtaining optimal or near-optimal solutions to FMS scheduling problems in relatively short computation times with the objective of minimizing the makespan. Its effectiveness is highlighted with excellent results that outperform previous methods on benchmark examples with flexible material handling systems, machine, and routing configurations. The approach can also serve as a decision support tool to assist production schedulers that require rapid and almost real-time responses to time-critical production scheduling on the shop floor.

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Section: Anytime Search Algorithmsmentioning

confidence: 99%

Section: Anytime Search Algorithmsmentioning

confidence: 99%

Section: Anytime Search Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Anytime heuristic search for scheduling flexible manufacturing systems: a timed colored Petri net approach

Baruwa

Piera

2014

Int J Adv Manuf Technol

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“…Anytime algorithms guarantee that the search produces the best solution obtained so far within the allotted computation time and they are expected to return better solutions when given more time. A recent study [50] adapted the anytime column search [51] to schedule FMS without considering DL situations. The proposed approach called anytime layered search (ALS) combines breadth-first iterative deepening A * search (BFIDA * ) with suboptimal breadth-first heuristic search (sBFHS) [52] and backtracking to provide a sequence of improving solutions.…”

mentioning

confidence: 99%

Deadlock-Free Scheduling Method for Flexible Manufacturing Systems Based on Timed Colored Petri Nets and Anytime Heuristic Search

Baruwa

Piera

Guasch

2015

IEEE Trans. Syst. Man Cybern, Syst.

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Abstract-This paper addresses the deadlock (DL)-free scheduling problem of flexible manufacturing systems (FMS) characterized by resource sharing, limited buffer capacity, routing flexibility, and the availability of material handling systems. The FMS scheduling problem is formulated using timed colored Petri net (TCPN) modeling where each operation has a certain number of preconditions, an estimated duration, and a set of postconditions. Based on the reachability analysis of TCPN modeling, we propose a new anytime heuristic search algorithm which finds optimal or near-optimal DL-free schedules with respect to makespan as the performance criterion. The methodology tackles the time-constrained problem of very demanding systems (high diversity production and make-to-order) in which computational time is a critical factor to produce optimal schedules that are DL-free. In such a rapidly changing environment and under tight customer due-dates, producing optimal schedules becomes intractable given the time limitations and the NP-hard nature of scheduling problems. The proposed anytime search algorithm combines breadth-first iterative deepening A * with suboptimal breadth-first heuristic search and backtracking. It guarantees that the search produces the best solution obtained so far within the allotted computation time and provides better solutions when given more time. The effectiveness of the approach is evaluated on a comprehensive benchmark set of DL-prone FMS examples and the computational results show the superiority of the proposed approach over the previous works.Index Terms-Anytime heuristic search, deadlock-free, flexible manufacturing systems (FMS), Petri nets (PN), reachability analysis, scheduling.

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