Journal of Optimization in Industrial Engineering最新文献_第9页

Nurse scheduling problem by considering fuzzy modeling approach to treat uncertainty on nurses’ preferences for working shifts and weekends off 采用模糊建模方法处理护士轮班和周末休假偏好的不确定性

Journal of Optimization in Industrial Engineering Pub Date : 2019-09-22 DOI: 10.22094/JOIE.2019.576759.1595

H. Jafari, H. Haleh

引用次数: 5

Developing a New Decision Support System to Manage Human Reliability based on HEART Method 基于HEART方法的人力可靠性管理决策支持系统研究

Journal of Optimization in Industrial Engineering Pub Date : 2019-07-21 DOI: 10.22094/JOIE.2019.553983.1521

R. Jamshidi

引用次数: 1

Production Planning and Control Strategies Used as A Gear Train for The Death and Birth of Manufacturing Industries 生产计划与控制策略作为制造业生死存亡的齿轮系

Journal of Optimization in Industrial Engineering Pub Date : 2019-07-01 DOI: 10.22094/JOIE.2018.774.1494

Alie Wube Dametew, Danile Ketaw, E. Frank

{"title":"Production Planning and Control Strategies Used as A Gear Train for The Death and Birth of Manufacturing Industries","authors":"Alie Wube Dametew, Danile Ketaw, E. Frank","doi":"10.22094/JOIE.2018.774.1494","DOIUrl":"https://doi.org/10.22094/JOIE.2018.774.1494","url":null,"abstract":"This study is conducted to developed innovative production planning and control strategies to manufacturing industries so as to improve production performance and competitiveness of basic metal sectors Though the study was conducted through field observation and questioner used as primary data and literature review on research articles, books, and electronic-sources which used as secondary data. While the questioner and filed observation data collection were done from two selected Ethiopian basic metal industries. Since the collected data were employed by both using descriptive and empirical analysis. Waste in the production process, poor plant layout systems, defective products, improper material requirement planning, deficiency on control and monitoring systems, insufficient inventory control, poor workflow strategies, null warehouse management systems, problems in information systems and information management strategies were investigated as the main challenges of developing the nation basic metal industries. As a result of these challenges, the performance and global competitiveness of local basic metal industries are poor and weak. As well the literature’ finding endorse that production planning and controls have gradual advancement in developed manufacturing industries but it is found to be at its infant stage in developing manufacturing industries. Due to these challenges and weak performances on the developing firms, the entire production process on the industries was declining, and then they approach to die. Though the new product planning and controlling strategies can bridge the gap and birth will begin within proper implementations of the model to basic metal industries.","PeriodicalId":36956,"journal":{"name":"Journal of Optimization in Industrial Engineering","volume":"12 1","pages":"21-32"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44731702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Using the Hybrid Model for Credit Scoring (Case Study: Credit Clients of microloans, Bank Refah-Kargeran of Zanjan, Iran) 使用信用评分的混合模型（案例研究：小额贷款的信贷客户，伊朗赞詹银行Refah Kargeran）

Journal of Optimization in Industrial Engineering Pub Date : 2019-07-01 DOI: 10.22094/JOIE.2019.574793.1583

A. Nazari, M. Mehregan, R. Tehrani

引用次数: 0

Three Hybrid Metaheuristic Algorithms for Stochastic Flexible Flow Shop Scheduling Problem with Preventive Maintenance and Budget Constraint 具有预防性维护和预算约束的随机柔性流水车间调度问题的三种混合元启发式算法

Journal of Optimization in Industrial Engineering Pub Date : 2019-07-01 DOI: 10.22094/JOIE.2018.242.1532

S. Raissi, R. Rooeinfar, V. Ghezavati

{"title":"Three Hybrid Metaheuristic Algorithms for Stochastic Flexible Flow Shop Scheduling Problem with Preventive Maintenance and Budget Constraint","authors":"S. Raissi, R. Rooeinfar, V. Ghezavati","doi":"10.22094/JOIE.2018.242.1532","DOIUrl":"https://doi.org/10.22094/JOIE.2018.242.1532","url":null,"abstract":"Stochastic flexible flow shop scheduling problem (SFFSSP) is one the main focus of researchers due to the complexity arises from inherent uncertainties and also the difficulty of solving such NP-hard problems. Conventionally, in such problems each machine’s job process time may encounter uncertainty due to their relevant random behaviour. In order to examine such problems more realistically, fixed interval preventive maintenance (PM) and budget constraint are considered.PM activity is a crucial task to reduce the production efficiency. In the current research we focused on a scheduling problem which a job is processed at the upstream stage and all the downstream machines get busy or alternatively PM cost is significant, consequently the job waits inside the buffers and increases the associated holding cost. This paper proposes a new more realistic mathematical model which considers both the PM and holding cost of jobs inside the buffers in the stochastic flexible flow shop scheduling problem. The holding cost is controlled in the model via the budget constraint. In order to solve the proposedmodel, three hybrid metaheuristic algorithms are introduced. They include a couple of well-known metaheuristic algorithms which have efficient quality solutions in the literature. The two algorithms of them constructed byincorporationof the particle swarm optimization algorithm (PSO) and parallel simulated annealing (PSA) methods under different random generation policies. The third one enriched based on genetic algorithm (GA) with PSA. To evaluate the performance of the proposed algorithms, different numerical examples are presented. Computational experiments revealed that the proposed algorithms embedboth desirable accuracy and CPU time. Among them, the PSO-PSAП outperforms than other algorithms in terms of makespan and CPU time especially for large size problems.","PeriodicalId":36956,"journal":{"name":"Journal of Optimization in Industrial Engineering","volume":"12 1","pages":"131-147"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44514786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Designing Tolerance of Assembled Components Using Weibull Distribution 用威布尔分布设计装配件公差

Journal of Optimization in Industrial Engineering Pub Date : 2019-07-01 DOI: 10.22094/JOIE.2018.751.1481

M. Movahedi, S. Seyedghasemi

{"title":"Designing Tolerance of Assembled Components Using Weibull Distribution","authors":"M. Movahedi, S. Seyedghasemi","doi":"10.22094/JOIE.2018.751.1481","DOIUrl":"https://doi.org/10.22094/JOIE.2018.751.1481","url":null,"abstract":"Tolerancing is one of the most important tools for planning, controlling, and improving quality in the industry. Tolerancing conducted by design engineers to meet customers’ needs is a prerequisite for producing high-quality products. Engineers use handbooks to conduct tolerancing. While use of statistical methods for tolerancing is not a new concept, engineers often use known distributions, including the normal distribution. However, if the statistical distribution of the given variable is unknown, a new statistical method will be employed to design tolerance. Therefore, in this study we want to offer a proper statistical method for determining tolerance. The use of statistical methods to design tolerance is not a new concept; however, flexible use of statistical distributions can enhance its performance. In this regard, Weibull distribution is proposed. To illustrate the proposed method first technical characteristics of production parts were selected randomly, and then manufacturing parameters were determined using maximum likelihood method. Finally, the Goodness of Fit test was used to ensure the accuracy of the obtained results.","PeriodicalId":36956,"journal":{"name":"Journal of Optimization in Industrial Engineering","volume":"12 1","pages":"179-188"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45864511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection Problem 不确定条件下基于欧几里得-豪斯多夫距离测度的分层群体妥协排序方法在设施选址问题中的应用

Journal of Optimization in Industrial Engineering Pub Date : 2019-07-01 DOI: 10.22094/JOIE.2016.270

S. Mousavi, H. Gitinavard, B. Vahdani, N. Foroozesh

{"title":"Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection Problem","authors":"S. Mousavi, H. Gitinavard, B. Vahdani, N. Foroozesh","doi":"10.22094/JOIE.2016.270","DOIUrl":"https://doi.org/10.22094/JOIE.2016.270","url":null,"abstract":"Proposing a hierarchical group compromise method can be regarded as a one of major multi-attributes decision-making tool that can be introduced to rank the possible alternatives among conflict criteria. Decision makers’ (DMs’) judgments are considered as imprecise or fuzzy in complex and hesitant situations. In the group decision making, an aggregation of DMs’ judgments and fuzzy group compromise ranking is more capable and powerful than the classical compromise ranking. This research extends a new hierarchical group compromise ranking methodology under a hesitant fuzzy (HF)environment to handle uncertainty, in which for the margin of error, the DMs could assign the opinions in several membership degrees for an element. The hesitant fuzzy set (HFS)is taken into account for the process of the proposed hierarchical group compromise ranking methodology, namely HFHG-CR, and for avoiding the data loss, the DMs’ opinions with risk preferences are considered for each step separately. Also, the Euclidean–Hausdorff distance measure is utilized in a new proposed index for calculating the average group score, worst group score and compromise measure regarding each DM. A new ranking index is presented for final compromise solution for the evaluation. Proposed HFHG-CR methodology is applied to a practical example for a facility location selection problem, i.e. cross-dock location problem, to show the validation and application.","PeriodicalId":36956,"journal":{"name":"Journal of Optimization in Industrial Engineering","volume":"12 1","pages":"93-105"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44005888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Diversified Particle Swarm Optimization for Hybrid Flowshop Scheduling 混合流水车间调度的多元粒子群优化

Journal of Optimization in Industrial Engineering Pub Date : 2019-07-01 DOI: 10.22094/JOIE.2018.671.1433

J. Behnamian

引用次数: 4

An Evolutionary Algorithm Based on a Hybrid Multi-Attribute Decision Making Method for the Multi-Mode Multi-Skilled Resource-constrained Project Scheduling Problem 基于混合多属性决策方法的多模式多技能资源约束项目调度进化算法

Journal of Optimization in Industrial Engineering Pub Date : 2019-07-01 DOI: 10.22094/JOIE.2018.556347.1531

A. Hosseinian, V. Baradaran

{"title":"An Evolutionary Algorithm Based on a Hybrid Multi-Attribute Decision Making Method for the Multi-Mode Multi-Skilled Resource-constrained Project Scheduling Problem","authors":"A. Hosseinian, V. Baradaran","doi":"10.22094/JOIE.2018.556347.1531","DOIUrl":"https://doi.org/10.22094/JOIE.2018.556347.1531","url":null,"abstract":"This paper addresses the multi-mode multi-skilled resource-constrained project scheduling problem. Activities of real world projects often require more than one skill to be accomplished. Besides, in many real-world situations, the resources are multi-skilled workforces. In presence of multi-skilled resources, it is required to determine the combination of workforces assigned to each activity. Hence, in this paper, a mixed-integer formulation called the MMSRCPSP is proposed to minimize the completion time of project. Since the MMSRCPSP is strongly NP-hard, a new genetic algorithm is developed to find optimal or near-optimal solutions in a reasonable computation time. The proposed genetic algorithm (PGA) employs two new strategies to explore the solution space in order to find diverse and high-quality individuals. Furthermore, the PGA uses a hybrid multi-attribute decision making (MADM) approach consisting of the Shannon’s entropy method and the VIKOR method to select the candidate individuals for reproduction. The effectiveness of the PGA is evaluated by conducting numerical experiments on several test instances. The outputs of the proposed algorithm is compared to the results obtained by the classical genetic algorithm, harmony search algorithm, and Neurogenetic algorithm. The results show the superiority of the PGA over the other three methods. To test the efficiency of the PGA in finding optimal solutions, the make-span of small size benchmark problems are compared to the optimal solutions obtained by the GAMS software. The outputs show that the proposed genetic algorithm has obtained optimal solutions for 70% of test problems.","PeriodicalId":36956,"journal":{"name":"Journal of Optimization in Industrial Engineering","volume":"12 1","pages":"155-178"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44766358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

The Preemptive Just-in-time Scheduling Problem in a Flow Shop Scheduling System 流车间调度系统中的抢占式准时调度问题

Journal of Optimization in Industrial Engineering Pub Date : 2019-07-01 DOI: 10.22094/JOIE.2017.499.11

J. Rezaeian, Sadegh Hosseini-Kia, I. Mahdavi

{"title":"The Preemptive Just-in-time Scheduling Problem in a Flow Shop Scheduling System","authors":"J. Rezaeian, Sadegh Hosseini-Kia, I. Mahdavi","doi":"10.22094/JOIE.2017.499.11","DOIUrl":"https://doi.org/10.22094/JOIE.2017.499.11","url":null,"abstract":"Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs. In this paper, just-in-time (JIT) flow shop scheduling problem with preemption and machine idle time assumptions is considered in which objective function is minimizing the sum of weighted earliness and tardiness. A new non-linear mathematical model is formulated for this problem and due to high complexity of the problem meta-heuristic approaches have been applied to solve the problem for finding optimal solution. The parameters of algorithms are set by Taguchi method. Each parameter is tested in three levels. By implementation of many problems with different sizes these levels are determined .The proposed model is solved by three meta-heuristic algorithms: genetic algorithm (GA), imperialist competitive algorithm (ICA) and hybrid of GA and ICA. To evaluate the performance of the proposed algorithms many test problems have been designed. The Computational results indicate the superiority of the performance of hybrid approach than GA and ICA in finding thebest solution in reasonable computational time.","PeriodicalId":36956,"journal":{"name":"Journal of Optimization in Industrial Engineering","volume":"12 1","pages":"79-92"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47031056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0