A novel metaheuristic method for simultaneous scheduling of machines and tools in multi machine FMS

Reddy, N. Sivarami; Ramamurthy, D. V.; Rao, K. Prahlada; Lalitha, M. Padma

doi:10.1049/cp.2016.1489

Cited by 7 publications

(6 citation statements)

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“…Costa et al 31 have developed a hybrid GA that implements a local search enhancement scheme to resolve "p" parts on "q" machines scheduling undertaking tool change activity triggered by tool wear. Sivarami Reddy et al 18 presented SOSA to deal with machines and tools joint scheduling to produce best optimal sequences with a copy of every type of tools in a MMFMS that minimize MSN and it is shown that SOSA outperforms the existing algorithms. Cristina et al 32 modeled and addressed the identical parallel machines problem with tooling constraints for minimizing MSN using an adaptive large neighborhood search metaheuristic(ALNS).…”

Section: Scheduling Of Machines and Toolsmentioning

confidence: 99%

“…38 It has been successfully applied to cope with engineering optimization problems. 18,[37][38][39][40][41][42] In the above references it is shown that SOSA is performing better than many other algorithms. The main advantage of SOSA is the absence of specific regulatory parameters compared to other meta-heuristic algorithms, simple and easy to implement.…”

Section: Scheduling Of Machines Agvs and Toolsmentioning

confidence: 99%

“…Sanches Sipoli et al 17 developed an adoptive GTA to work out the scheduling of production systems considering the concurrent use of computers and AGVs for minimum MSN. Reddy et al 18 addressed the machines and AGVs concurrent scheduling in a MMFMS by using symbiotic organisms search algorithm (SOSA) for minimization of MSN and it is made known that the results of SOSA are promising. Lin James et al 19 proposed a simulation based optimization L-GA OCBA to address the concurrent scheduling of vehicles and machines considering vehicle congestion, dead lock and stochastic processing times.…”

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confidence: 99%

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Optimum scheduling of machines, automated guided vehicles and tools without tool delay in a multi‐machine flexible manufacturing system using symbiotic organisms search algorithm

Lalitha

Narapureddy

Dwivedula³

et al. 2022

Concurrency and Computation

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This article deals with machines, automated guided vehicles (AGVs) and tools simultaneous scheduling in multimachine flexible manufacturing system (FMS) with the lowest possible number of copies of every tool type without tool delay considering jobs' transport times among machines to minimize makespan (MSN). The tools are kept in a central tool magazine (CTM), which is shared by and serves many machines. Tool transporter (TT) and AGVs shift tools and jobs among machines respectively. This concurrent scheduling problem is extremely complex in nature as it involves determining the lowest possible tool copies of every type of tool, allocation of AGVs and tools copies to job-operations, job-operations sequencing on machines, and associated trip operations including the dead heading trip and loaded trip times of AGVs. This paper proposes nonlinear mixed integer programming (MIP) formulation to model this problem and symbiotic organisms search algorithm (SOSA) for solving this problem. Verification is carried out using an industrial problem in a manufacturing firm. The results show that employing two copies for one tool type and one copy each for the remaining tool types results in no tool delay and reduction in MSN which causes a reduction in cost, and SOSA is providing better solution than Jaya algorithm.

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Section: Scheduling Of Machines and Toolsmentioning

confidence: 99%

Section: Scheduling Of Machines Agvs and Toolsmentioning

confidence: 99%

mentioning

confidence: 99%

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Optimum scheduling of machines, automated guided vehicles and tools without tool delay in a multi‐machine flexible manufacturing system using symbiotic organisms search algorithm

Lalitha

Narapureddy

Dwivedula³

et al. 2022

Concurrency and Computation

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“…Compared to other approaches, such as GA, DE, bees algorithm, PSO and particle bee algorithm, it has been stated that SOSA gave better results. Sivarami Reddy et al (2016) proposed SOSA to deal with machines and tools simultaneous scheduling where operations are performed on specific machines (SMTWSM) to produce best optimal sequences with a copy of every type of tools in a MMFMS that minimize makespan and it is shown that SOSA outperforms the existing algorithms. Sonmez et al (2016) proposed SOSA to solve the dynamic economic dispatch with valve-point effects problem and shown that SOSA produces better results and has good convergence than other methods.…”

Section: I1 Literature Reviewmentioning

confidence: 99%

Simultaneous scheduling of machines and tools in a multi machine FMS with alternative routing using symbiotic organisms search algorithm

Reddy¹,

Lalitha

Pandey³

et al. 2021

JER is an international, peer-reviewed journal that publishes f

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This paper deals with simultaneous scheduling of machines and tools with alternate machines in a multi machine flexible manufacturing system (FMS) to minimize makespan (MS). Only one copy of each type of tools is made available due to economic restrictions and the tools are stored in a central tool magazine (CTM) that shares with and serves for several machines. The problem is to select machines from alternate machines for job-operations, allocation of tools to job-operations and job-operations’ sequencing on machines for MS minimization. This paper presents a nonlinear mixed integer programming (MIP) formulation to model the combined scheduling of machines and tools with alternate machines and a symbiotic organisms search algorithm (SOSA) built on the symbiotic interaction strategies that organisms employ to continue to exist in the ecosystem for solving the scheduling of machines and tools with alternate machines. The results have been tabulated, analyzed. It is observed that there is a reduction in MS when the alternate machines are considered for job-operation.

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“…Cheng and Huang 18 formulate an unrelated PMSP as a mixed integer programming (MIP) model and develop a modiﬁed genetic algorithm. Reddy et al 19 consider simultaneous scheduling of machines, tools and many other resources to generate optimal sequences by using a symbiotic organisms search (SOS) algorithm. In conclusion, different kinds of algorithms are improved, and fusion algorithms are also proposed to solve these hybrid scheduling optimization problems.…”

Section: Introductionmentioning

confidence: 99%

A Tabu-GA-based parallel machine scheduling with restrained tool resources

Wang

Zou

Wang

2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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In flexible manufacturing systems, disordered parallel machine scheduling may cause interruptions in the production line; thus, a reasonable scheduling plan beneﬁts proﬁts of manufacturing. In the literature, the operation sequence, the operation assignment, the tool scheduling, and the tool switching problems have been studied with unlimited resources. However, in practical manufacturing process, a scheduling problem along with these problems with restrained resources should be studied to make scheduling solutions more performable. There are a number of operations processed on a group of parallel machines, and each operation requires a set of tools where the tool copy number and tool service life are limited. The objective of this problem is to minimize the make-span with restrained resources. This article studies a parallel machine scheduling problem combining operation scheduling, tool scheduling and restrained resources, which benefit the real industry. A Tabu-Genetic Algorithm is proposed to find the optimal solution. In small size problem, the proposed method can achieve similar results whereas the mixed integer programming approach can obtain the exact solution. However, in large size problem, the latter cannot obtain the solutions within acceptable times, whereas the proposed method can ﬁnd solutions within reasonable times. This algorithm performs better when compared to Tabu search algorithm and genetic algorithm in selecting local and global optima.

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A novel metaheuristic method for simultaneous scheduling of machines and tools in multi machine FMS

Cited by 7 publications

References 0 publications

Optimum scheduling of machines, automated guided vehicles and tools without tool delay in a multi‐machine flexible manufacturing system using symbiotic organisms search algorithm

Optimum scheduling of machines, automated guided vehicles and tools without tool delay in a multi‐machine flexible manufacturing system using symbiotic organisms search algorithm

Simultaneous scheduling of machines and tools in a multi machine FMS with alternative routing using symbiotic organisms search algorithm

A Tabu-GA-based parallel machine scheduling with restrained tool resources

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