scholarly journals Research on multi-objective optimal scheduling considering the balance of labor workload distribution

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255737
Author(s):  
Zhengyu Hu ◽  
Wenrui Liu ◽  
Shengchen Ling ◽  
Kuan Fan
Keyword(s):  
Flow Shop ◽  
Programming Model ◽  
Nonlinear Integer Programming ◽  
Flow Shop Scheduling ◽  
Nsga Ii ◽  
Shop Scheduling ◽  
Proposed Model ◽  
Minimum Delay ◽  
Workload Distribution ◽  
Minimum Delay Time

In order to solve the problem of unbalanced workload of employees in parallel flow shop scheduling, a method of job standard balance is proposed to describe the work balance of employees. The minimum delay time of completion and the imbalance of employee work are taken as the two goals of the model. A bi-objective nonlinear integer programming model is proposed. NSGA-II-EDSP, NSGA-II-KES, and NSGA-II-QKES heuristic rule algorithms are designed to solve the problem. A number of computational experiments of different sizes are conducted, and compared with solutions generated by NSGA-II. The experimental results show the advantages of the proposed model and method, which error is reduced 14.56%, 15.16% and 15.67%.

scholarly journals Integration of Lot Sizing and Flow Shop Scheduling with Lot Streaming

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Navid Mortezaei ◽  
Norzima Zulkifli
Keyword(s):  
Flow Shop ◽  
Lot Sizing ◽  
Flow Shop Scheduling ◽  
Mixed Integer ◽  
Lot Streaming ◽  
Optimal Sequence ◽  
Shop Scheduling ◽  
Proposed Model ◽  
Integer Linear Model ◽  
No Wait

We will develop a mathematical model for the integration of lot sizing and flow shop scheduling with lot streaming. We will develop a mixed-integer linear model for multiple products lot sizing and lot streaming problems. Mixed-integer programming formulation is presented which will enable the user to find optimal production quantities, optimal inventory levels, optimal sublot sizes, and optimal sequence simultaneously. We will use numerical example to show practicality of the proposed model. We test eight different lot streaming problems: (1) consistent sublots with intermingling, (2) consistent sublots and no intermingling between sublots of the products (without intermingling), (3) equal sublots with intermingling, (4) equal sublots without intermingling, (5) no-wait consistent sublots with intermingling, (6) no-wait equal sublots with intermingling, (7) no-wait consistent sublots without intermingling, and (8) no-wait equal sublots without intermingling. We showed that the best makespan can be achieved through the consistent sublots with intermingling case.

scholarly journals A two-phase fuzzy programming model for a complex bi-objective no-wait flow shop scheduling

2012 ◽  
Vol 3 (4) ◽  
pp. 617-626 ◽  
Author(s):  
Mahdi Naderi-Beni ◽  
Reza Tavakkoli-Moghaddam ◽  
Bahman Naderi ◽  
Ehsan Ghobadian ◽  
Alireza Pourrousta
Keyword(s):  
Flow Shop ◽  
Programming Model ◽  
Fuzzy Programming ◽  
Flow Shop Scheduling ◽  
Two Phase ◽  
Shop Scheduling ◽  
No Wait ◽  
Fuzzy Programming Model

Study on Multi-Objective Optimization of Hybrid Flow Shop Scheduling Problem

2014 ◽  
Vol 1082 ◽  
pp. 529-534
Author(s):  
Zheng Ying Lin ◽  
Wei Zhang
Keyword(s):  
Flow Shop ◽  
Economic Benefits ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Scheduling Problem ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Shop Scheduling ◽  
Multi Objective ◽  
Hybrid Flow Shop Scheduling

Due to several mutual conflicting optimized objectives in the hybrid flow shop scheduling problem, its optimized model, including three objectives of make-span, flow-time and tardiness, was firstly set up, instead of the single optimized objective. Furthermore, in order to improve the optimized efficiency and parallelism, after comparing the normal multi-objective optimized methods, an improved NSGA-II algorithm with external archive strategy was proposed. Finally, taking a piston production line as example, its performance was tested. The result showed that the multi-objective optimization of hybrid flow shop scheduling based on improved NSGA-II provided managers with a set of feasible solutions for selection in accordance to their own preference. Therefore the decision could be made more scientific and efficient, and thus brings to the factory more economic benefits.

scholarly journals Two-machine flow shop with synchronized periodic maintenance

2019 ◽  
Vol 53 (1) ◽  
pp. 351-365 ◽  
Author(s):  
Issam Krimi ◽  
Rachid Benmansour ◽  
Saïd Hanafi ◽  
Nizar Elhachemi
Keyword(s):  
Variable Neighborhood Search ◽  
Flow Shop ◽  
Programming Model ◽  
Flow Shop Scheduling ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Shop Scheduling ◽  
Availability Constraints ◽  
Periodic Maintenance ◽  
One Machine

In the literature, some works deal with the two-machine flow shop scheduling problem under availability constraints. Most of them consider those constraints only for one machine at a time and also with limited unavailability periods. In this work, we were interested by the unlimited periodic and synchronized maintenance applied on both machines. The problem is NP-hard. We proposed a mixed integer programming model and a variable neighborhood search for solving large instances in order to minimize the makespan. Computational experiments show the efficiency of the proposed methods.

scholarly journals A DE-LS Metaheuristic Algorithm for Hybrid Flow-Shop Scheduling Problem considering Multiple Requirements of Customers

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yingjia Sun ◽  
Xin Qi
Keyword(s):  
Differential Evolution ◽  
Flow Shop ◽  
Programming Model ◽  
Flow Shop Scheduling ◽  
Mixed Integer ◽  
Hybrid Flow Shop ◽  
Scheduling Problem ◽  
Metaheuristic Algorithm ◽  
Shop Scheduling ◽  
Hybrid Flow Shop Scheduling

In this paper, we address a hybrid flow-shop scheduling problem with the objective of minimizing the makespan and the cost of delay. The concerned problem considers the diversity of the customers’ requirements, which influences the procedures of the productions and increases the complexity of the problem. The features of the problem are inspired by the real-world situations, and the problem is formulated as a mixed-integer programming model in the paper. In order to tackle the concerned problem, a hybrid metaheuristic algorithm with Differential Evolution (DE) and Local Search (LS) (denoted by DE-LS) has been proposed in the paper. The differential evolution is a state-of-the-art metaheuristic algorithm which can solve complex optimization problem in an efficient way and has been applied in many fields, especially in flow-shop scheduling problem. Moreover, the study not only combines the DE and LS, but also modifies the mutation process and provides the novel initialization process and correction strategy of the approach. The proposed DE-LS has been compared with four variants of algorithms in order to justify the improvements of the proposed algorithm. Experimental results show that the superiority and robustness of the proposed algorithm have been verified.

Optimizing Bi-Criteria Permutation Flow Shop Scheduling Problem by Improved NSGA III

2018 ◽  
Author(s):  
Ronghua Meng ◽  
Yunqing Rao ◽  
Qiang Luo
Keyword(s):  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Computational Time ◽  
Test Problems ◽  
Scheduling Problem ◽  
Nsga Ii ◽  
Solution Quality ◽  
Shop Scheduling ◽  
Permutation Flow Shop Scheduling ◽  
Permutation Flow Shop

This paper addresses a bi-objective distribution permutation flow shop scheduling problem (FSP) with setup times aiming to minimize the makespan and the total tardiness. It is very difficult to obtain an optimal solution by using traditional approaches in reasonable computational time. This paper presents an appropriate non-dominated sorting Genetic Algorithm III based on the reference point. The NEH strategy is applied into the generation of the initial solution set. To validate the performance of the NEH strategy improved NSGA III (NNSGA III) on solution quality and diversity level, various test problems are carried out. Three algorithms, including NSGA II, NEH strategy improved NSGA II(NNSGA II) and NNSGA III are utilized to solve this FSP. Experimental results suggest that the proposed NNSGA III outperforms the other algorithms on the Inverse Generation Distance metric, and the distribution of Pareto solutions are improved excellently.

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