Graph Coloring based Optimized Algorithm for Resource Utilization in Examination Scheduling

Saharan, Sandeep; Kumar, Ravinder

doi:10.18576/amis/100338

Cited by 4 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Their work focuses on measuring the degree of satisfaction of constraints and they try to achieve even distribution of courses. Authors in [2] exploit graph coloring to generate exam schedules by following a two phase scheme such that in phase one they schedule exams regardless of number of available seats in halls. Then, in phase two, they check if the number of needed seats in the generated schedule exceeds the number of available seats.…”

Section: A Graph Coloringmentioning

confidence: 99%

See 1 more Smart Citation

A Hybrid Exam Scheduling Technique based on Graph Coloring and Genetic Algorithms Targeted towards Student Comfort

Hassan¹,

Qtaish²,

Abuhamdeh³

et al. 2019

ijacsa

View full text Add to dashboard Cite

Scheduling is one of the vital activities needed in various aspects of life. It is also a key factor in generating exam schedules for academic institutions. In this paper we propose an exam scheduling technique that combines graph coloring and genetic algorithms. On one hand, graph coloring is used to order sections such that sections that are difficult to schedule comes first and accordingly scheduled first which helps in increasing the probability of generating valid schedules. On the other hand, we use genetic algorithms to search more effectively for more optimized schedules within the large search space. We propose a two-stage fitness function that is targeted toward increasing student comfort. We also investigate the effect and potency of the crossover operator and the mutation operator. Our experiments are conducted on a realistic dataset and the results show that a mutation only hybrid approach has a low cost and converges faster toward more optimized schedules.

show abstract

Section: A Graph Coloringmentioning

confidence: 99%

“…Several life activities exploit scheduling to ensure efficient and proper operation including exam scheduling that is used in academic institutions for producing high quality exam schedules [1], [2], [3].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Exam Scheduling Technique based on Graph Coloring and Genetic Algorithms Targeted towards Student Comfort

Hassan¹,

Qtaish²,

Abuhamdeh³

et al. 2019

ijacsa

View full text Add to dashboard Cite

show abstract

“…Appointment scheduling is an important determinant of efficiency, timely access to health services, and patient satisfaction [ 2 ]. In recent years, medical appointment scheduling has grown comprehensively in the literature, including outpatient scheduling [ 3 – 5 ], surgery scheduling [ 6 – 8 ], and medical examination scheduling [ 9 – 11 ]. Regarding the review papers [ 2 , 12 ], the appointment scheduling system can be regarded as a queuing system, of which the simplest case is when all scheduled patients arrive punctually in their appointment times and a single doctor serves them with stochastic processing times.…”

Section: Literature Reviewmentioning

confidence: 99%

Online Appointment Scheduling for a Nuclear Medicine Department in a Chinese Hospital

Xiao

Luo

Zhao

et al. 2018

Computational and Mathematical Methods in Medicine

View full text Add to dashboard Cite

Nuclear medicine, a subspecialty of radiology, plays an important role in proper diagnosis and timely treatment. Multiple resources, especially short-lived radiopharmaceuticals involved in the process of nuclear medical examination, constitute a unique problem in appointment scheduling. Aiming at achieving scientific and reasonable appointment scheduling in the West China Hospital (WCH), a typical class A tertiary hospital in China, we developed an online appointment scheduling algorithm based on an offline nonlinear integer programming model which considers multiresources allocation, the time window constraints imposed by short-lived radiopharmaceuticals, and the stochastic nature of the patient requests when scheduling patients. A series of experiments are conducted to show the effectiveness of the proposed strategy based on data provided by the WCH. The results show that the examination amount increases by 29.76% compared with the current one with a significant increase in the resource utilization and timely rate. Besides, it also has a high stability for stochastic factors and bears the advantage of convenient and economic operation.

show abstract

“…χ(G), the chromatic number of G, is defined as the minimum number of colors required for V(G) so that no two adjacent vertices are of the same color [2]. The graph coloring problem (GCP) finds the value for χ(G) and applies it to register allocation, channel assignment, image segmentation, resource utilization, and scheduling [3][4][5][6][7][8][9][10]. With the increasing values of n, the complexity of determining χ(G) also increases.…”

Section: Introductionmentioning

confidence: 99%

“…Tabu search [17], backtracking [18], branch and bound [11], evolutionary algorithm [19][20][21], branch and cut [22], particle swarm optimization (PSO) [23][24][25][26], ant colony optimization (ACO) [27], local and cuckoo search [28,29] are some existing methods for finding χ(G). Some recent applications of GCP are selective graph coloring [30,31], signed graphs coloring [32,33], scheduling, and resource allocation [7][8][9][10][34][35][36][37][38]. In comparison to other methods, GA is useful for solving multi-objective optimization problems with vast search space.…”

Section: Introductionmentioning

confidence: 99%

Complexity Analysis and Stochastic Convergence of Some Well-known Evolutionary Operators for Solving Graph Coloring Problem

Marappan

Sethumadhavan

2020

Mathematics

View full text Add to dashboard Cite

The graph coloring problem is an NP-hard combinatorial optimization problem and can be applied to various engineering applications. The chromatic number of a graph G is defined as the minimum number of colors required to color the vertex set V(G) so that no two adjacent vertices are of the same color, and different approximations and evolutionary methods can find it. The present paper focused on the asymptotic analysis of some well-known and recent evolutionary operators for finding the chromatic number. The asymptotic analysis of different crossover and mutation operators helps in choosing the better evolutionary operator to minimize the problem search space and computational complexity. The choice of the right genetic operators facilitates an evolutionary algorithm to achieve faster convergence with lesser population size N through an adequate distribution of promising genes. The selection of an evolutionary operator plays an essential role in reducing the bounds for minimum color obtained so far for some of the benchmark graphs. This research also focuses on the necessary and sufficient conditions for the global convergence of evolutionary algorithms. The stochastic convergence of recent evolutionary operators for solving graph coloring is newly analyzed.

show abstract

Graph Coloring based Optimized Algorithm for Resource Utilization in Examination Scheduling

Cited by 4 publications

References 5 publications

A Hybrid Exam Scheduling Technique based on Graph Coloring and Genetic Algorithms Targeted towards Student Comfort

A Hybrid Exam Scheduling Technique based on Graph Coloring and Genetic Algorithms Targeted towards Student Comfort

Online Appointment Scheduling for a Nuclear Medicine Department in a Chinese Hospital

Complexity Analysis and Stochastic Convergence of Some Well-known Evolutionary Operators for Solving Graph Coloring Problem

Contact Info

Product

Resources

About