scholarly journals Bicriterion Optimization for Flow Shop with a Learning Effect Subject to Release Dates

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ji-Bo Wang ◽  
Jian Xu ◽  
Jing Yang
Keyword(s):  
Pareto Front ◽  
Learning Effect ◽  
Flow Shop ◽  
Search Tree ◽  
Release Dates ◽  
Processing Times ◽  
Flow Shop Problem ◽  
Speed Up ◽  
Bicriterion Optimization ◽  
Time Subject

This paper investigates a two-machine flow shop problem with release dates in which the job processing times are variable according to a learning effect. The bicriterion is to minimize the weighted sum of makespan and total completion time subject to release dates. We develop a branch-and-bound (B&B) algorithm to solve the problem by using a dominance property, several lower bounds, and an upper bound to speed up the elimination process of the search tree. We further propose a multiobjective memetic algorithm (MOMA), enhanced by an initialization strategy and a global search strategy, to obtain the Pareto front of the problem. Computational experiments are also carried out to examine the effectiveness and the efficiency of the B&B algorithm and the MOMA algorithm.

scholarly journals Minimizing the Makespan for a Two-Stage Three-Machine Assembly Flow Shop Problem with the Sum-of-Processing-Time Based Learning Effect

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Win-Chin Lin
Keyword(s):  
Learning Effect ◽  
Flow Shop ◽  
Optimal Solutions ◽  
Work Experiences ◽  
Two Stage ◽  
Processing Times ◽  
Production Environments ◽  
Flow Shop Problem ◽  
Iterated Greedy ◽  
Machine Assembly

Two-stage production process and its applications appear in many production environments. Job processing times are usually assumed to be constant throughout the process. In fact, the learning effect accrued from repetitive work experiences, which leads to the reduction of actual job processing times, indeed exists in many production environments. However, the issue of learning effect is rarely addressed in solving a two-stage assembly scheduling problem. Motivated by this observation, the author studies a two-stage three-machine assembly flow shop problem with a learning effect based on sum of the processing times of already processed jobs to minimize the makespan criterion. Because this problem is proved to be NP-hard, a branch-and-bound method embedded with some developed dominance propositions and a lower bound is employed to search for optimal solutions. A cloud theory-based simulated annealing (CSA) algorithm and an iterated greedy (IG) algorithm with four different local search methods are used to find near-optimal solutions for small and large number of jobs. The performances of adopted algorithms are subsequently compared through computational experiments and nonparametric statistical analyses, including the Kruskal–Wallis test and a multiple comparison procedure.

scholarly journals A Two-Stage Three-Machine Flow Shop Assembly Problem Mixed with a Controllable Number and Sum-of-Processing Times-Based Learning Effect by Simulated Annealing Algorithms

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Shang-Chia Liu
Keyword(s):  
Simulated Annealing ◽  
Processing Time ◽  
Learning Effect ◽  
Flow Shop ◽  
Service Industries ◽  
Two Stage ◽  
Processing Times ◽  
Assembly Scheduling ◽  
Assembly Problem ◽  
Annealing Algorithms

The two-stage assembly scheduling problem is widely used in industrial and service industries. This study focuses on the two-stage three-machine flow shop assembly problem mixed with a controllable number and sum-of-processing times-based learning effect, in which the job processing time is considered to be a function of the control of the truncation parameters and learning based on the sum of the processing time. However, the truncation function is very limited in the two-stage flow shop assembly scheduling settings. Thus, this study explores a two-stage three-machine flow shop assembly problem with truncated learning to minimize the makespan criterion. To solve the proposed model, we derive several dominance rules, lemmas, and lower bounds applied in the branch-and-bound method. On the other hand, three simulated annealing algorithms are proposed for finding approximate solutions. In both the small and large size number of job situations, the SA algorithm is better than the JS algorithm in this study. All the experimental results of the proposed algorithm are presented on small and large job sizes, respectively.

A Note on Flow Shop Scheduling with the Effects of Learning and Deterioration

2014 ◽  
Vol 513-517 ◽  
pp. 2149-2152
Author(s):  
Yu Ping Niu ◽  
Ji Bo Wang
Keyword(s):  
Learning Effect ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Shop Scheduling ◽  
Processing Times ◽  
Polynomially Solvable ◽  
Machine Scheduling Problems ◽  
Completion Times ◽  
Sum Of Completion Times

In this note, we consider the machine scheduling problems with the effects of learning and deterioration. In this model, job processing times are defined by functions dependent on their starting times and positions in the sequence. The scheduling objectives are makespan, sum of completion times. It is shown that even with the introduction of learning effect and deterioration jobs to job processing times, several flow shop problems remain polynomially solvable.

A Note on Scheduling Jobs with Extended Sum-of-Processing-Times-Based and Position-Based Learning Effect

2015 ◽  
Vol 32 (02) ◽  
pp. 1550001 ◽  
Author(s):  
Yu-Ping Niu ◽  
Long Wan ◽  
Ji-Bo Wang
Keyword(s):  
Learning Effect ◽  
Flow Shop ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Processing Times ◽  
Effect Model ◽  
Special Cases ◽  
Machine Scheduling Problems

The note deals with machine scheduling problems with a more general learning effect model, i.e., the actual job processing time is a function of the sum of the function of the processing times of the jobs already processed and job position. We show that some single machine scheduling problems are still polynomially solvable under the proposed model. We also show that some special cases of the flow shop scheduling problems can be solved in polynomial time.

scholarly journals Optimal Results and Numerical Simulations for Flow Shop Scheduling Problems

2012 ◽  
Vol 2012 ◽  
pp. 1-9
Author(s):  
Tao Ren ◽  
Yuandong Diao ◽  
Xiaochuan Luo
Keyword(s):  
Local Search ◽  
Completion Time ◽  
Flow Shop ◽  
Asymptotic Optimality ◽  
Flow Shop Scheduling ◽  
Release Dates ◽  
Scheduling Problems ◽  
Improvement Strategy ◽  
Shop Scheduling ◽  
Flow Shop Problem

This paper considers them-machine flow shop problem with two objectives: makespan with release dates and total quadratic completion time, respectively. For Fm|rj|Cmax, we prove the asymptotic optimality for any dense scheduling when the problem scale is large enough. For Fm‖ΣCj2, improvement strategy with local search is presented to promote the performance of the classical SPT heuristic. At the end of the paper, simulations show the effectiveness of the improvement strategy.

Sign in / Sign up

Export Citation Format

Share Document