Open shop scheduling problem with a multi-skills resource constraint: a genetic algorithm and an ant colony optimisation approach

Campos, Guillermo; Dugardin, Frédéric; Yalaoui, Farouk; Kelly, Russell

doi:10.1080/00207543.2015.1126371

Cited by 27 publications

(15 citation statements)

References 52 publications

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“…Evolutionary heuristic methods make it possible to model dynamic integrated forward/reverse logistics network for 3rd party logistics (3PL) providers, where GA optimizes the network plan to help in the determination of resource plans for capacities of technical and human resources [9]. Ant colony based heuristics support open shop scheduling problems with a multi-skills resource constraint [10] and the solution of operating room surgery scheduling [11]. Scheduling of temporary and skilled-workers in dynamic cellular manufacturing systems can be solved by hybrid algorithms [12].…”

Section: State Of the Art In Human Resource Researchmentioning

confidence: 99%

Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy

2018

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Manufacturing and service processes are composed of several elements: Technical, financial, logistics, information and human resources. Staff deployment and staffing is an essential problem in the human resource management domain because the structure of employees would be continuously in an optimal relationship to the jobs to be performed. This paper proposes a conceptual model for the analysis of human resource deployment processes. After a systematic literature review, it was found that algorithms are important tools for the design and control of human resource problems since a wide range of models determines an optimization problem. According to that, the main focus of this research is the modelling and analysis of human resource deployment processes of manufacturing companies using Markov-chain mathematics, also taking into account the absorbing phenomena of employees’ promotion. The main contribution of this article includes the model framework of Markov-chain simulation of a human resource deployment problem; the mathematical description of different human resource deployment strategies with subdiagonal and superdiagonal promotion matrices; the computational results of the described model with different datasets and scenarios. In the case of a given human resource strategy, the Markovian human resource deployment process of a company was analyzed. The analyzed model was the HR deployment of assembly line operators in a multinational company, including six levels of promotion. The results of the scenario analysis show that promotion and recruitment rates have a great impact on the future employees’ structure.

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Section: State Of the Art In Human Resource Researchmentioning

confidence: 99%

Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy

2018

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“…Due to the numerous parameters to set in an ACO and their strong influence on the quality of results, Yalaoui et al (2010) and Yalaoui et al (2013) decided to apply fuzzy logic controllers to cope with the tuning of parameters. As they got good results, we decide to adapt this solution method to the open shop scheduling problem with resource constraints, developing a fuzzy-ACO algorithm which presents the parameters and modifications of an ACO that have already been explained by Campos-Ciro et al (2014). The complete algorithm procedure is detailed hereafter:…”

Section: Proposed Fuzzy Ant Colony Optimization Algorithmmentioning

confidence: 99%

“…We expose the problem with a mixed integer linear programming model that is used in Campos-Ciro et al (2014) to get optimal solutions of the described problem. The parameters related to the lists of skills are inspired by other authors who solved the multi-skill scheduling problems as Montoya (2012).…”

Section: Problem Formulationmentioning

confidence: 99%

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A fuzzy ant colony optimization to solve an open shop scheduling problem with multi-skills resource constraints

et al. 2015

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An open shop scheduling problem based on a mechanical workshop is described here. The main objective is to find the sequence of jobs which minimizes the total flow time. For that reason, we first formulate the problem as a mixed integer linear programming model which considers different resource constraints related to the personnel assignment. Resource skills and their availability are required to process tasks. A mathematical model is described and solved optimally. Besides that, a fuzzy ant colony optimization method is proposed due to the difficulty to fix the different parameters of an ACO and improve the quality of the solution. Finally, some computational experiments are defined using the references of the literature to get efficiency of ant colony optimisation. A first kind of tests are related to the small-sized instances allowing to evaluate the general performance of the model and the algorithm while a second one involves the large-size instances showing a further evaluation of the algorithm.

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“…Reference [27] used the ant colony algorithm to solve the rebalancing problem of the production line. In solving the scheduling problem of the production floor, reference [28] used genetic algorithms and ant colony algorithms to solve scheduling problems. Considering the problem of cargo recovery, reference [29] designed a hybrid ant colony algorithm to solve the problem of path optimization in such cases.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Three Intelligent Algorithms on Route Selection of Fishbone Layout

Zhou

Shi

et al. 2019

Sustainability

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The Internet of Things (IoT) has become an important strategy in the current round of global economic growth and technological development and provides a new path for the intelligent development of the logistics industry. With the development of the economy, the demand for logistics benefits is becoming more important. The appropriate use of technologies related to IoT to improve logistics efficiency, such as cloud computing, mobile computing and data mining, has become a topic of considerable research interest. Picking operations are currently an extremely important and cumbersome aspect of logistics center tasks. To shorten the picking distance and improve work efficiency, this paper uses the genetic algorithm, ant colony algorithm and cuckoo algorithm to optimize the picking path in a fishbone-layout warehouse and establishes an optimized model of the warehouse picking path under the fishbone layout. Data-mining technology is used to simulate the model and obtain the simulation data under the condition of multiple orders. The results provide a theoretical basis for the study of the fishbone-layout picking path model and has certain practical significance for the efficient operation of logistics enterprises. Through optimization, it is conducive to the sustainable development of enterprises and to achieving long-term profitability.

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Open shop scheduling problem with a multi-skills resource constraint: a genetic algorithm and an ant colony optimisation approach

Cited by 27 publications

References 52 publications

Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy

Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy

A fuzzy ant colony optimization to solve an open shop scheduling problem with multi-skills resource constraints

Performance Analysis of Three Intelligent Algorithms on Route Selection of Fishbone Layout

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