Hybrid discrete differential evolution algorithm for biobjective cyclic hoist scheduling with reentrance

Yan, Pengyu; Wang, Guanhua; Che, Ada; Li, Yaoyiran

doi:10.1016/j.cor.2016.06.011

Cited by 32 publications

(10 citation statements)

References 34 publications

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“…To verify the applicability of the proposed algorithm, both benchmark and randomly generated instances were used in the experimental studies. , which can be found in [7,18,[37][38][39]. Table 1 gives the experimental results for five benchmark instances obtained with our algorithm and CPLEX software, in terms of the number of remaining possible after applying Rule 1 (Nb.…”

Section: Resultsmentioning

confidence: 99%

A Hybrid Quantum Evolutionary Algorithm with Improved Decoding Scheme for a Robotic Flow Shop Scheduling Problem

Lei¹,

Manier²,

Manier³

et al. 2017

Mathematical Problems in Engineering

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We aim at solving the cyclic scheduling problem with a single robot and flexible processing times in a robotic flow shop, which is a well-known optimization problem in advanced manufacturing systems. The objective of the problem is to find an optimal robot move sequence such that the throughput rate is maximized. We propose a hybrid algorithm based on the Quantum-Inspired Evolutionary Algorithm (QEA) and genetic operators for solving the problem. The algorithm integrates three different decoding strategies to convert quantum individuals into robot move sequences. The Q-gate is applied to update the states of Q-bits in each individual. Besides, crossover and mutation operators with adaptive probabilities are used to increase the population diversity. A repairing procedure is proposed to deal with infeasible individuals. Comparison results on both benchmark and randomly generated instances demonstrate that the proposed algorithm is more effective in solving the studied problem in terms of solution quality and computational time.

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Section: Resultsmentioning

confidence: 99%

A Hybrid Quantum Evolutionary Algorithm with Improved Decoding Scheme for a Robotic Flow Shop Scheduling Problem

Lei¹,

Manier²,

Manier³

et al. 2017

Mathematical Problems in Engineering

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“…However, metaheuristics inspired from natural systems are capable of obtaining high quality solutions within moderate computational time, serving as a good alternative when dealing with real-world problems. DE algorithm initially proposed by Storn and Price [23] has emerged as a simple yet efficient metaheuristic with successful application in many fields such as the job-shop scheduling problem [24], the vehicle routing problem [25], the forecast problem [26], the cyclic hoist scheduling problem [27], the reactive power management problem [28], and the parallel batch processing machine scheduling problem [29]. Therefore, in this paper, we propose a new DE algorithm combining DE with multiple improvement strategies to solve the RMSP problem.…”

Section: Solution Methodsmentioning

confidence: 99%

Mathematical Model and Algorithm for the Reefer Mechanic Scheduling Problem at Seaports

Zhang

Song

2017

Discrete Dynamics in Nature and Society

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With the development of seaborne logistics, the international trade of goods transported in refrigerated containers is growing fast. Refrigerated containers, also known as reefers, are used in transportation of temperature sensitive cargo, such as perishable fruits. This trend brings new challenges to terminal managers, that is, how to efficiently arrange mechanics to plug and unplug power for the reefers (i.e., tasks) at yards. This work investigates the reefer mechanics scheduling problem at container ports. To minimize the sum of the total tardiness of all tasks and the total working distance of all mechanics, we formulate a mathematical model. For the resolution of this problem, we propose a DE algorithm which is combined with efficient heuristics, local search strategies, and parameter adaption scheme. The proposed algorithm is tested and validated through numerical experiments. Computational results demonstrate the effectiveness and efficiency of the proposed algorithm.

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“…Other works adopting hybrid methods consider specific CHSP settings. For instance, [6] propose a two-stage approach for two hoists consisting of a custom heuristic followed by IP, while [23] hybridise two forms of evolutionary algorithm.…”

Section: Related Workmentioning

confidence: 99%

A new constraint programming model and solving for the cyclic hoist scheduling problem

Wallace

Yorke-Smith

2020

Constraints

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The cyclic hoist scheduling problem (CHSP) is a well-studied optimisation problem due to its importance in industry. Despite the wide range of solving techniques applied to the CHSP and its variants, the models have remained complicated and inflexible, or have failed to scale up with larger problem instances. This article re-examines modelling of the CHSP and proposes a new simple, flexible constraint programming formulation. We compare current state-of-the-art solving technologies on this formulation, and show that modelling in a high-level constraint language, MiniZinc, leads to both a simple, generic model and to computational results that outperform the state of the art. We further demonstrate that combining integer programming and lazy clause generation, using the multiple cores of modern processors, has potential to improve over either solving approach alone.

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Hybrid discrete differential evolution algorithm for biobjective cyclic hoist scheduling with reentrance

Cited by 32 publications

References 34 publications

A Hybrid Quantum Evolutionary Algorithm with Improved Decoding Scheme for a Robotic Flow Shop Scheduling Problem

A Hybrid Quantum Evolutionary Algorithm with Improved Decoding Scheme for a Robotic Flow Shop Scheduling Problem

Mathematical Model and Algorithm for the Reefer Mechanic Scheduling Problem at Seaports

A new constraint programming model and solving for the cyclic hoist scheduling problem

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