Optimization of integrated employee timetabling and Hybrid Job Shop Scheduling under time lag constraints

2014 ◽  
Author(s):  
Mohamed Frihat ◽  
Cherif Sadfi ◽  
Atidel B. Hadj-Alouane
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Time Lag ◽  
Shop Scheduling ◽  
Employee Timetabling

scholarly journals Solving an integrated employee timetabling and job-shop scheduling problem via hybrid branch-and-bound

2009 ◽  
Vol 36 (8) ◽  
pp. 2330-2340 ◽  
Author(s):  
Christian Artigues ◽  
Michel Gendreau ◽  
Louis-Martin Rousseau ◽  
Adrien Vergnaud
Keyword(s):  
Branch And Bound ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Employee Timetabling

A modified biogeography-based optimization algorithm with improved mutation operator for job shop scheduling problem with time lags

2020 ◽  
Author(s):  
Madiha Harrabi ◽  
Olfa Belkahla Driss ◽  
Khaled Ghedira
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Optimization Problems ◽  
Time Lag ◽  
Initial Population ◽  
Time Lags ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Combinatorial Optimization Problems

Abstract This paper addresses the job shop scheduling problem including time lag constraints. This is an extension of the job shop scheduling problem with many applications in real production environments, where extra (minimum and maximum) delays can be introduced between successive operations of the same job. It belongs to a category of problems known as NP-hard problem due to large solution space. Biogeography-based optimization is an evolutionary algorithm which is inspired by the migration of species between habitats, recently proposed by Simon in 2008 to optimize hard combinatorial optimization problems. We propose a hybrid biogeography-based optimization (HBBO) algorithm for solving the job shop scheduling problem with additional time lag constraints with minimization of total completion time. In the proposed HBBO, the effective greedy constructive heuristic is adapted to generate the initial population of habitat. Moreover, a local search metaheuristic is investigated in the mutation step in order to ameliorate the solution quality and enhance the diversity of the population. To assess the performance of HBBO, a series of experiments on well-known benchmark instances for job shop scheduling problem with time lag constraints is performed.

Solving Job Shop Scheduling Problem Based on Employee Availability Constraint

2013 ◽  
Vol 376 ◽  
pp. 197-206 ◽  
Author(s):  
G. Ramya ◽  
M. Chandrasekaran
Keyword(s):  
Job Scheduling ◽  
Job Shop ◽  
Heuristic Algorithms ◽  
Job Shop Scheduling ◽  
Performance Criteria ◽  
Labor Costs ◽  
Shuffled Frog Leaping Algorithm ◽  
Shop Scheduling ◽  
Shuffled Frog Leaping ◽  
Employee Timetabling

Manufacturing System is enabled with an excellent knowledge on production plan, proper scheduling of machinery process, employee timetabling and labor costs. Heuristic algorithms are developed to bring optimized results in stipulated time with respect to optimum schedule. This article deals with minimizing the maximum completion time (makespan) based on job scheduling and minimization of labor costs based on employee workload with Shuffled Frog Leaping Algorithm and Sheep Flock Heredity Model Algorithm. The labor costs minimization and makespan which is to find a schedule that satisfies the organizations rules, employees preferences, due date and customers. The formulation of assigning workload for employees is concerned with assigning number of employees into a given set of shifts over a fixed period of time and week task. The main problem attempts to minimize labor costs based on performance criteria and assigning the loads equally among all employees. Several local search methods and heuristics algorithms has been proposed in many research on Job shop scheduling. The Results are compared with other heuristics in terms of makespan, idle time and Labor costs the Shuffled Frog Leaping algorithm performs result oriented than other Heuristics Algorithm.

Memory Based Lamarckian Evolutionary Algorithm for Job Shop Scheduling Problem

2011 ◽  
Vol 21 (12) ◽  
pp. 3082-3093
Author(s):  
Zhu-Chang XIA ◽  
Fang LIU ◽  
Mao-Guo GONG ◽  
Yu-Tao QI
Keyword(s):  
Evolutionary Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling
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