scholarly journals SEMI-ON-LINE PARALLEL MACHINES SCHEDULING UNDER KNOWN TOTAL AND LARGEST PROCESSING TIMES

2005 ◽  
Vol 48 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Soo Young Chang ◽  
Hark Chin Hwang ◽  
Jongho Park
Keyword(s):  
Parallel Machines ◽  
Processing Times ◽  
Line Parallel ◽  
Parallel Machines Scheduling ◽  
On Line

Tardiness Scheduling with Fuzzy Processing Time Using Tabu Search

2012 ◽  
Vol 472-475 ◽  
pp. 2279-2282
Author(s):  
Hong Bing Yang ◽  
Wen Chao Li ◽  
Xian Ping Guan ◽  
Fei Zhou
Keyword(s):  
Tabu Search ◽  
Parallel Machines ◽  
Programming Model ◽  
Fuzzy Theory ◽  
Difficult Problem ◽  
Total Tardiness ◽  
Mixed Integer ◽  
Processing Times ◽  
Fuzzy Processing Times ◽  
Parallel Machines Scheduling

In this paper, we address unrelated parallel machines scheduling problem with fuzzy processing times considering the minimization of the total tardiness cost. The tardiness credibility index of jobs is given to estimate the possibility of job’s tardiness, and a mixed integer programming model (MIP) is formulated for total tardiness cost based on fuzzy theory. Solving the MIP problem is NP-hard, thus a tabu search is designed to solve such a difficult problem. The results of computational test show the feasibility and effectiveness of the developed model and algorithm.

scholarly journals Fuzzy Scheduling Problem on Unrelated Parallel Machine in JIT Production System

2020 ◽  
pp. 17-33
Author(s):  
Javad Rezaeian ◽  
Samir Mohammad-Hosseini ◽  
Sara Zabihzadeh ◽  
Keyvan Shokoufi
Keyword(s):  
Parallel Machines ◽  
Programming Model ◽  
Statistical Tests ◽  
Setup Times ◽  
Scheduling Problem ◽  
Due Dates ◽  
Processing Times ◽  
Fuzzy Environment ◽  
Parallel Machines Scheduling ◽  
Dependent Setup Times

This paper deals with unrelated parallel machines scheduling problem with sequence dependent setup times under fully fuzzy environment to minimize total weighted fuzzy earliness and tardiness penalties, which belongs to NP-hard class. Due to inherent uncertainty in Processing times, setup times and due dates of jobs, they are considered here with triangular and trapezoidal fuzzy numbers in order to take into account the unpredictability of parameters in practical settings. Although this study is not the first one to study on fuzzy parallel machines scheduling problem, it advances this area of research in three fields: (1) it selects a fuzzy environment to cover the whole area of the considered problem not just part of it, and also, it chooses an appropriate fuzzy method based on an in-depth investigation of the effect of spread of fuzziness on the variables; (2) It introduces a mathematical programming model for the addressed problem as an exact method; and (3) due to NP-hardness of the problem, it develops an existing algorithm in the literature for the considered problem through extensive simulated experiments and statistical tests on the same benchmark problem test by proposing a genetic algorithm (GA) and a modified simulated annealing (SA) methods to solve this hard combinatorial optimization problem. The result shows the superiority of our modified SA.

scholarly journals Scheduling Jobs with Variable Job Processing Times on Unrelated Parallel Machines

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Guang-Qian Zhang ◽  
Jian-Jun Wang ◽  
Ya-Jing Liu
Keyword(s):  
Resource Allocation ◽  
Parallel Machines ◽  
Waiting Times ◽  
Optimal Schedule ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Unrelated Parallel Machines ◽  
Scheduling Problems ◽  
Processing Times ◽  
Parallel Machines Scheduling

munrelated parallel machines scheduling problems with variable job processing times are considered, where the processing time of a job is a function of its position in a sequence, its starting time, and its resource allocation. The objective is to determine the optimal resource allocation and the optimal schedule to minimize a total cost function that dependents on the total completion (waiting) time, the total machine load, the total absolute differences in completion (waiting) times on all machines, and total resource cost. If the number of machines is a given constant number, we propose a polynomial time algorithm to solve the problem.

scholarly journals Scheduling jobs with stochastically ordered processing times on parallel machines to minimize expected flowtime

1986 ◽  
Vol 23 (03) ◽  
pp. 841-847 ◽  
Author(s):  
R. R. Weber ◽  
P. Varaiya ◽  
J. Walrand
Keyword(s):  
Processing Time ◽  
Parallel Machines ◽  
Preemptive Scheduling ◽  
Total Reward ◽  
Processing Times ◽  
Identical Machines ◽  
Scheduling Strategies

A number of jobs are to be processed using a number of identical machines which operate in parallel. The processing times of the jobs are stochastic, but have known distributions which are stochastically ordered. A reward r(t) is acquired when a job is completed at time t. The function r(t) is assumed to be convex and decreasing in t. It is shown that within the class of non-preemptive scheduling strategies the strategy SEPT maximizes the expected total reward. This strategy is one which whenever a machine becomes available starts processing the remaining job with the shortest expected processing time. In particular, for r(t) = – t, this strategy minimizes the expected flowtime.

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