scholarly journals Competitive Two-Agent Scheduling with Learning Effect and Release Times on a Single Machine

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Der-Chiang Li ◽  
Peng-Hsiang Hsu
Keyword(s):  
Single Machine ◽  
Learning Effect ◽  
Optimal Solution ◽  
Total Weighted Completion Time ◽  
Optimal Solutions ◽  
Release Times ◽  
Agent Scheduling ◽  
Weighted Completion Time ◽  
Dominance Properties ◽  
Annealing Algorithms

The learning effect has gained much attention in the scheduling research recently, where many researchers have focused their problems on only one optimization. This study further addresses the scheduling problem in which two agents compete to perform their own jobs with release times on a common single machine with learning effect. The aim is to minimize the total weighted completion time of the first agent, subject to an upper bound on the maximum lateness of the second agent. We propose a branch-and-bound approach with several useful dominance properties and an effective lower bound for searching the optimal solution and three simulated-annealing algorithms for the near-optimal solutions. The computational results show that the proposed algorithms perform effectively and efficiently.

A SINGLE-MACHINE TWO-AGENT SCHEDULING PROBLEM BY GA APPROACH

2012 ◽  
Vol 29 (02) ◽  
pp. 1250013 ◽  
Author(s):  
SHUENN-REN CHENG
Keyword(s):  
Single Machine ◽  
Completion Time ◽  
Learning Effect ◽  
Control Parameter ◽  
Optimal Schedule ◽  
Total Weighted Completion Time ◽  
Scheduling Problem ◽  
Processing Times ◽  
Agent Scheduling ◽  
Weighted Completion Time

A single-machine two-agent scheduling problem with a truncation learning effect is being addressed in the study. The truncation learning effect means that the actual processing time of a job is a function of the sum of processing times of already scheduled jobs and a control parameter. The aim is to find an optimal schedule to minimize the total weighted completion time of jobs of the first agent under the circumstances that no tardy job is allowed for the second agent. A branch-and-bound and three heuristic-based genetic algorithms (GAs) are proposed to solve the problem. Also presented in the study are the computational results of all proposed algorithms.

scholarly journals Single-Machine Scheduling with Accelerating Learning Effects

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
T. C. E. Cheng ◽  
Shih-Chang Tseng ◽  
Peng-Jen Lai ◽  
Wen-Chiung Lee
Keyword(s):  
Single Machine ◽  
Completion Time ◽  
Learning Effect ◽  
Single Machine Scheduling ◽  
Total Tardiness ◽  
Total Weighted Completion Time ◽  
Learning Effects ◽  
Optimal Solutions ◽  
New Model ◽  
Weighted Completion Time

Scheduling with learning effects has been widely studied. However, there are situations where the learning effect might accelerate. In this paper, we propose a new model where the learning effect accelerates as time goes by. We derive the optimal solutions for the single-machine problems to minimize the makespan, total completion time, total weighted completion time, maximum lateness, maximum tardiness, and total tardiness.

scholarly journals A Single-Machine Two-Agent Scheduling Problem by a Branch-and-Bound and Three Simulated Annealing Algorithms

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Shangchia Liu ◽  
Wen-Hsiang Wu ◽  
Chao-Chung Kang ◽  
Win-Chin Lin ◽  
Zhenmin Cheng
Keyword(s):  
Simulated Annealing ◽  
Branch And Bound ◽  
Single Machine ◽  
Completion Time ◽  
Optimal Solution ◽  
Total Completion Time ◽  
Practical Applications ◽  
Processing Resource ◽  
Agent Scheduling ◽  
Annealing Algorithms

In the field of distributed decision making, different agents share a common processing resource, and each agent wants to minimize a cost function depending on its jobs only. These issues arise in different application contexts, including real-time systems, integrated service networks, industrial districts, and telecommunication systems. Motivated by its importance on practical applications, we consider two-agent scheduling on a single machine where the objective is to minimize the total completion time of the jobs of the first agent with the restriction that an upper bound is allowed the total completion time of the jobs for the second agent. For solving the proposed problem, a branch-and-bound and three simulated annealing algorithms are developed for the optimal solution, respectively. In addition, the extensive computational experiments are also conducted to test the performance of the algorithms.

Genetic Algorithm for a Two-Agent Scheduling Problem with Truncated Learning Consideration

2014 ◽  
Vol 31 (06) ◽  
pp. 1450046 ◽  
Author(s):  
Wen-Hsiang Wu ◽  
Yunqiang Yin ◽  
Shuenn-Ren Cheng ◽  
Peng-Hsiang Hsu ◽  
Chin-Chia Wu
Keyword(s):  
Processing Time ◽  
Optimal Solution ◽  
Total Weighted Completion Time ◽  
Scheduling Problem ◽  
Learning Effects ◽  
Research Attention ◽  
Multiple Agent ◽  
Agent Scheduling ◽  
Dominance Properties ◽  
Actual Processing Time

Scheduling with learning effects has received lots of research attention lately. However, the multiple-agent setting with learning consideration is relatively limited. On the other hand, the actual processing time of a job under an uncontrolled learning effect will drop to zero precipitously as the number of the jobs already processed increases. This is rather absurd in reality. Based on these observations, this paper considers a single-machine two-agent scheduling problem in which the actual processing time of a job depends not only on the job's scheduled position, but also on a control parameter. The objective is to minimize the total weighted completion time of jobs from the first agent with the restriction that no tardy job is allowed for the second agent. A branch-and-bound algorithm incorporated with several dominance properties and lower bounds is proposed to derive the optimal solution for the problem. In addition, genetic algorithms (GAs) are also provided to obtain the near-optimal solution. Finally, a computational experiment is conducted to evaluate the performance of the proposed algorithms.

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.

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