scholarly journals Performance enhancement of numerical approaches for scheduling problem on machine single

2021 ◽  
Vol 12 (7) ◽  
pp. 1739-1750
Author(s):  
Omar Selt
Keyword(s):  
Completion Time ◽  
Performance Enhancement ◽  
Optimal Solution ◽  
Solution Space ◽  
Single Machine Scheduling ◽  
The Other ◽  
Weighted Sum ◽  
Scheduling Problem ◽  
Diversification Strategies ◽  
Numerical Approaches

In this paper, we consider a single-machine scheduling problem, with the aim of minimizing the weighted sum of the  completion time. This problem is NP-hard, making the search for an optimal solution very difficult. In this frame, two heuristics (H1), (H2) and metaheuristic tabu search are suggested.To improve the performance of this techniques, we used, on one hand, different diversification strategies (TES1 and TES2) with the aim of exploring unvisited regions of the solution space. On the other hand, we suggested three types of neighborhoods (neighborhood by swapping, neighborhood by insertion and neighborhood by blocks).It must be noted that tasks movement can be within one period or between different periods.

Single Machine Two-Agent Scheduling with Deteriorating Jobs

2016 ◽  
Vol 33 (05) ◽  
pp. 1650034 ◽  
Author(s):  
Zhenyou Wang ◽  
Cai-Min Wei ◽  
Yu-Bin Wu
Keyword(s):  
Single Machine ◽  
Completion Time ◽  
Processing Time ◽  
Deteriorating Jobs ◽  
Single Machine Scheduling ◽  
Total Weighted Completion Time ◽  
Scheduling Problem ◽  
Agent Scheduling ◽  
Polynomially Solvable ◽  
Weighted Completion Time

This paper deals with the single machine scheduling problem with deteriorating jobs in which there are two distinct families of jobs (i.e., two-agent) pursuing different objectives. In this model the processing time of a job is defined as a function that is proportional to a linear function of its stating time. For the following three scheduling criteria: minimizing the makespan, minimizing the total weighted completion time, and minimizing the maximum lateness, we show that some basic versions of the problem are polynomially solvable. We also establish the conditions under which the problem is computationally hard.

A Hybrid Differential Evolution Scheduling Algorithm to Heterogeneous Distributed System

2014 ◽  
Vol 631-632 ◽  
pp. 271-275
Author(s):  
Yan Kang ◽  
Zhong Min Wang ◽  
Ying Lin ◽  
Xiang Yun Guo
Keyword(s):  
Differential Evolution ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Differential Evolution Algorithm ◽  
Optimal Solution ◽  
Solution Space ◽  
Greedy Heuristic ◽  
Particle Swarm Algorithm ◽  
Scheduling Problem ◽  
Heuristic Strategy

This paper presents a differential evolution algorithm with designed greedy heuristic strategy to solve the task scheduling problem. The static task scheduling problem is NP-complete and is a critic issue in parallel and distributed computing environment. A vector consists of a task permutation assigned to each individual in the target population by using DE mutation and crossover operators. A heuristic strategy is used to generate the feasible solutions as there a lot of infeasible solutions in the solution space as the size of the problem increase. And the strategies of the particle swarm algorithm are employed to modify the DE crossover operator for speeding up the search to optimal solution. And then, the individual is replaced with the corresponding target individual if it is global best or local best in terms of fitness. The performance of the algorithm is illustrated by comparing with the existing effectively scheduling algorithms. The performances of the proposed algorithms are tested on the benchmark and compared to the best-known solutions available. The computational results demonstrate that effectively and efficiency of the presented algorithm.

scholarly journals Solving No-Wait Flow Shop Scheduling Problem Based on Discrete Wolf Pack Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Rongshen Lai ◽  
Bo Gao ◽  
Wenguang Lin
Keyword(s):  
Flow Shop ◽  
Optimal Solution ◽  
Solution Space ◽  
Flow Shop Scheduling ◽  
Searching Behavior ◽  
Scheduling Problem ◽  
Application Research ◽  
Shop Scheduling ◽  
No Wait ◽  
The Individual

Aiming at the no-wait flow shop scheduling problem with the goal of minimizing the maximum makespan, a discrete wolf pack algorithm has been proposed. First, the methods for solving the no-wait flow shop scheduling problem and the application research of the wolf pack algorithm were summarized, and it was pointed out that there was lack of research on the application of the wolf pack algorithm to solve the no-wait flow shop scheduling problem. According to the analysis of characteristics of the no-wait flow shop scheduling problem, the individual wolf was coded by a decimal integer; wolf searching behavior was realized through the exchange of different code bits in the individual wolf, and the continuous code segment of the head wolf was randomly selected to replace the corresponding code of the fierce wolf, by which the behaviors of wolves raiding and sieging were realized, and the population was updated according to the rule of “survival of the strong.” In particular, to fully explore the potential optimal solution in the solution space, loop operations were added to the wandering, summoning, and siege processes. Finally, based on a comparison with the leapfrog algorithm and the genetic algorithm, the effectiveness of the algorithm was verified.

A Branch-and-Bound Algorithm for Two-Agent Scheduling with Learning Effect and Late Work Criterion

2018 ◽  
Vol 35 (05) ◽  
pp. 1850037 ◽  
Author(s):  
Shang-Chia Liu ◽  
Jiahui Duan ◽  
Win-Chin Lin ◽  
Wen-Hsiang Wu ◽  
Jan-Yee Kung ◽  
...  
Keyword(s):  
Branch And Bound ◽  
Learning Effect ◽  
Optimal Schedule ◽  
Optimal Solution ◽  
Single Machine Scheduling ◽  
Branch And Bound Algorithm ◽  
Scheduling Problem ◽  
Late Work ◽  
Processing Times ◽  
Agent Scheduling

This paper studies a two-agent single-machine scheduling problem with sum-of-processing-times-based learning consideration. The goal is to find an optimal schedule to minimize the total late work of the first agent subject to the restriction that the maximum lateness of the second agent has an upper bound. For this problem, a branch-and-bound algorithm along with several dominances and a lower bound is developed to find the optimal solution, and a tabu algorithm with several improvements is proposed to find the near-optimal solution. Computational experiments are provided to further measure the performance of the proposed algorithms.

Sign in / Sign up

Export Citation Format

Share Document