A real-time order acceptance and scheduling approach for permutation flow shop problems

Rahman, Humyun Fuad; Sarker, Ruhul A.; Essam, Daryl

doi:10.1016/j.ejor.2015.06.018

Cited by 64 publications

(56 citation statements)

References 44 publications

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“…The problem requires repeated optimization procedures as each new order arrives since it includes dynamic aspects (e.g., customer orders are randomly placed). The suggested approach in [21] showed a stable performance despite the dynamic situation. Lei et al [22] proposed a GA-based framework for real-time dynamic voltage scaling with multiple objectives.…”

Section: Introductionmentioning

confidence: 99%

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The Dynamic Enterprise Network Composition Algorithm for Efficient Operation in Cloud Manufacturing

2016

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Abstract:As a service oriented and networked model, cloud manufacturing (CM) has been proposed recently for solving a variety of manufacturing problems, including diverse requirements from customers. In CM, on-demand manufacturing services are provided by a temporary production network composed of several enterprises participating within an enterprise network. In other words, the production network is the main agent of production and a subset of an enterprise network. Therefore, it is essential to compose the enterprise network in a way that can respond to demands properly. A properly-composed enterprise network means the network can handle demands that arrive at the CM, with minimal costs, such as network composition and operation costs, such as participation contract costs, system maintenance costs, and so forth. Due to trade-offs among costs (e.g., contract cost and opportunity cost of production), it is a non-trivial problem to find the optimal network enterprise composition. In addition, this includes probabilistic constraints, such as forecasted demand. In this paper, we propose an algorithm, named the dynamic enterprise network composition algorithm (DENCA), based on a genetic algorithm to solve the enterprise network composition problem. A numerical simulation result is provided to demonstrate the performance of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

“…Rahman et al [21] suggested a GA-based approach to solve the permutation flow shop scheduling problem. The problem requires repeated optimization procedures as each new order arrives since it includes dynamic aspects (e.g., customer orders are randomly placed).…”

Section: Introductionmentioning

confidence: 99%

The Dynamic Enterprise Network Composition Algorithm for Efficient Operation in Cloud Manufacturing

2016

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“…The reactive methods such as the shortest processing time (SPT) rule, the first come first serve (FCFS) rule, and the longest processing time (LPT) rule can be easily used to schedule jobs in real time. Right shifting (RS) strategy and real-time (RT) strategy are also reactive methods for coping with newly arrived orders [12]. RS and RT are two strategies which attach new orders to the end of the existing schedule.…”

Section: Related Workmentioning

confidence: 99%

“…Many studies [5,11] focus on the static environment which simplifies the problem constraint. However, more attention should be paid to dynamic aspects that frequently occurred in reality such as new order arrival [12,13], machine breakdown [14], and rush order [15]. It is typical in today's mass customization that new orders frequently arrive into factories.…”

Section: Introductionmentioning

confidence: 99%

“…The uncertainties in terms of job types, job numbers, arrival times, due dates, etc. have created significant challenges [12,16], which increases the complexity of the scheduling problem significantly. This happens in warehouses as well, and the problem is defined online order batching problems [17][18][19][20], in which new orders arrive frequently and stochastically, and scheduling or rescheduling should respond immediately upon their arrival.…”

Section: Introductionmentioning

confidence: 99%

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New meta-heuristic for dynamic scheduling in permutation flowshop with new order arrival

Liu

Jin

Price

2018

Int J Adv Manuf Technol

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Permutation flowshop scheduling problem (PFSP) has attracted lots of attention from both academia and industry as it finds many applications especially for today's mass customization. The PFSP is proved NP-hard, and the dynamic uncertainties such as stochastic new order arrivals significantly increase the problem complexity and difficulty. Many enterprises often struggle to make decisions on accepting new orders and setting due dates for them due to lack of effective scheduling methods. To fill in the knowledge gap, this paper is to propose a new meta-heuristic algorithm which is based on a new enhanced destruction and construction method and a novel repair method while adopting the architecture of the iterated greedy algorithm. Statistical tests were conducted and results show that the new algorithm outperforms existing ones. The maximum completion time of the new order

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Order Acceptance Policy for Make-To-Order Supply Chain

Ding

2019

Studies in Big Data

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A real-time order acceptance and scheduling approach for permutation flow shop problems

Cited by 64 publications

References 44 publications

The Dynamic Enterprise Network Composition Algorithm for Efficient Operation in Cloud Manufacturing

The Dynamic Enterprise Network Composition Algorithm for Efficient Operation in Cloud Manufacturing

New meta-heuristic for dynamic scheduling in permutation flowshop with new order arrival

Order Acceptance Policy for Make-To-Order Supply Chain

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