Flow shop scheduling to minimize the total completion time with a permanently present operator: Models and ant colony optimization metaheuristic

Li, Xiangyong; Baki, Mohammed Fazle; Aneja, Y. P.

doi:10.1016/j.cor.2010.04.009

Cited by 12 publications

(7 citation statements)

References 25 publications

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“…Anticipatory and non-anticipatory setup times are addressed by [56], minimising the makespan, and also considering dismounting times. The problem with m machines and a single server has been solved by [5] for total completion times' minimisation, but in this case, the server is responsible for both processing and setup operations. The authors have addressed the problem with non-anticipatory and sequence-independent setup times.…”

Section: Problem Description and Backgroundmentioning

confidence: 99%

“…In addition, in several situations, the processing of jobs may also require the use of other resources (such as, e.g., raw materials, human resources, or setup tools), denoted as 'secondary' ( [2]). Among these types of secondary resources, the use of servers is very common in the real manufacturing industry [3]: examples can be found in flexible manufacturing systems [4]; in scheduling problems with versatile machines and assembly components [5]; in computer-controlled material handling systems [6]; in biomass truck scheduling problems in the context of supply chain optimisation [7]; and in container terminals [8]. Servers are secondary resources that are in charge of carrying out setups between jobs or families of jobs.…”

Section: Introductionmentioning

confidence: 99%

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The Permutation Flow Shop Scheduling Problem with Human Resources: MILP Models, Decoding Procedures, NEH-Based Heuristics, and an Iterated Greedy Algorithm

et al. 2022

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In this paper, we address the permutation flow shop scheduling problem with sequence-dependent and non-anticipatory setup times. These setups are performed or supervised by multiple servers, which are renewable secondary resources (typically human resources). Despite the real applications of this kind of human supervision and the growing attention paid in the scheduling literature, we are not aware of any previous study on the problem under consideration. To cover this gap, we start theoretically addressing the problem by: proposing three mixed-integer linear programming models to find optimal solutions in the problem; and proposing different decoding procedures to code solutions in approximated procedures. After that, the best decoding procedure is used to propose a new mechanism that generates 896 different dispatching rules, combining different measures, indicators, and sorting criteria. All these dispatching rules are embedded in the traditional NEH algorithm. Finally, an iterated greedy algorithm is proposed to find near-optimal solutions. By doing so, we provide academics and practitioners with efficient methods that can be used to obtain exact solutions of the problem; applied to quickly schedule jobs and react under changes; used for initialisation or embedded in more advanced algorithms; and/or easily updated and implemented in real manufacturing scenarios.

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Section: Problem Description and Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Permutation Flow Shop Scheduling Problem with Human Resources: MILP Models, Decoding Procedures, NEH-Based Heuristics, and an Iterated Greedy Algorithm

et al. 2022

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“…To minimize total completion time in a no-wait two-machine flow-shop, Shyu et al (2004) designed some specific features including a heuristic for initializing the initial pheromone, a hybrid state transition rule and a hybrid local search. Li et al (2011) dealt with the minimization of the sum of completion time in a sequence-dependent setups permutational flowshop. The authors used a timelimited dynamic programming algorithm to perform a post-optimization strategy.…”

Section: Introductionmentioning

confidence: 99%

A new hybrid ant colony algorithm for scheduling of no-wait flowshop

Riahi

Kazemi

2016

Oper Res Int J

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In this paper, the no-wait flow shop scheduling problem under makespan and flowtime criteria is addressed. The no-wait flowshop is a variant of the wellknown flowshop scheduling problem where all processes follow the previous one without any interruption for operations of a job. Owing to the problem is known to be NP-hard for more than two machines, a hybrid meta-heuristic algorithm based on ant colony optimization (ACO) and simulated annealing (SA) algorithm is improved. First, at each step, due to the characteristic of ACO algorithm that include solution construction and pheromone trail updating, some different areas of search space are checked and best solution is selected. Then, to enhance the quality and diversity of the solution and finding best neighbor of this solution, a novel SA is presented. Moreover, a new principle is applied for global pheromone update based on the probability function like SA algorithm. The proposed approach solution is compared with several the state-of-the-art algorithms in the literature. The reported results show that the proposed algorithms are effective and the new approach for local search in ACO algorithm is efficient for solving the no-wait flow shop problem. Then, we employed another hybrid ACO algorithm based on hybridization of ACO with variable neighborhood search (VNS) and compare the results given by two proposed algorithms. These results show that our new hybrid provides better results than ACO-VNS algorithm.

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“…This supports the use of heuristic and meta-heuristics procedures that are proposed in DRC scheduling as they are capable of providing a feasible solution in a reasonable amount of time. Li et al (2011) presented a metaheuristic to minimise the total completion time with permanently present operators in a flow shop production system. ElMaraghy (2000) developed a genetic algorithm where multiple performance measures and dispatching rules were taken into account.…”

Section: Introductionmentioning

confidence: 99%

Simulated annealing approach to solve dual resource constrained job shop scheduling problems: layout impact analysis on solution quality

Faccio

Ries

Saggiorno

2015

IJMOR

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Real-world manufacturing systems are operating subject to a substantial level of resource constraints. One characteristic model that considers the combination of human and machine resource constraints is called dual resource constrained (DRC). In this context a number of machines n mach is managed by a selection of operators n op , with typically n op ≤ n mach.. A real life case study for an Italian manufacturing company is introduced that uses a set of identical parallel machines being operated by a set of operators. Each job is scheduled to one machine with corresponding loading and unloading process times. A simulated annealing approach is proposed to solve the DRC job shop scheduling problem. A sensitivity analysis is conducted for a selection of algorithm-specific parameters used to solve characteristic DRC layouts. Being characteristic for the just-in-time (JIT) production environment, the high variability in job times has also been taken into account. The results show that the selected layout n mach. /n op ratio strongly influences the production system performance. The impact of the ratio of constrained resources has been analysed for different layouts, showing that simulated annealing performs better for single resource constrained problems while also demonstrating that this trend is not symmetrical for different layouts, either operator or machine constrained.

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Flow shop scheduling to minimize the total completion time with a permanently present operator: Models and ant colony optimization metaheuristic

Cited by 12 publications

References 25 publications

The Permutation Flow Shop Scheduling Problem with Human Resources: MILP Models, Decoding Procedures, NEH-Based Heuristics, and an Iterated Greedy Algorithm

The Permutation Flow Shop Scheduling Problem with Human Resources: MILP Models, Decoding Procedures, NEH-Based Heuristics, and an Iterated Greedy Algorithm

A new hybrid ant colony algorithm for scheduling of no-wait flowshop

Simulated annealing approach to solve dual resource constrained job shop scheduling problems: layout impact analysis on solution quality

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