Modeling and Applications in Operations Research

Cover
Half Title
Series
Title
Copyright
Contents
Acknowledgments
Biography of editors
List of contributors
1 Ant colony optimization algorithm for the university course timetabling problem using events based on groupings of students
	1.1 Introduction
	1.2 Related work
	1.3 Statement of university course timetabling problem
	1.4 Ant colony optimization
	1.5 The proposed algorithm
	1.6 Experimental results
		1.6.1 Experiments on Socha’s benchmark dataset
		1.6.2 Experiments on ITC2007 benchmark dataset
	1.7 Conclusions
	References
2 Genetic optimization and their applications
	2.1 Introduction
		2.1.1 Difficulties faced
		2.1.2 Evolutionary algorithms
	2.2 Classical optimization techniques
		2.2.1 Single variable function optimization
		2.2.2 Multi-variable function optimization
		2.2.3 A general optimization algorithm
	2.3 Modern optimization techniques
		2.3.1 Simulated annealing
		2.3.2 Particle swarm optimization
		2.3.3 Ant colony optimization
		2.3.4 Honey bee optimization
		2.3.5 Genetic algorithms
	2.4 Proposed method
		2.4.1 Input
		2.4.2 Convolution
		2.4.3 Genetic optimizer for CNN (GOCNN)
		2.4.4 Case study on FER
	2.5 Conclusion
	References
3 Different variants of unreliable server: an economic approach
	3.1 Introduction
	3.2 Service system with server breakdown
	3.3 Service system with working breakdown of the server
	3.4 Service system with customer impatience, WB, service pressure condition, and threshold recovery policy
	3.5 Special cases
	3.6 Cost analysis
		3.6.1 Steady-state analysis
		3.6.2 Cost function
		3.6.3 Quasi-Newton method
	3.7 Numerical results and discussion
	3.8 Conclusion
	References
4 Multi-objective fuzzy linear programming problem with fuzzy decision variables: a geometrical approach
	4.1 Introduction
	4.2 Basic preliminaries
	4.3 Multi-objective fuzzy linear programming problem
	4.4 Solution procedures
	4.5 Numerical example
	4.6 Conclusion
	References
5 On approximation of piecewise linear membership functions and its application to solve solid transportation problem with fuzzy cost coefficients
	5.1 Introduction
	5.2 Fuzzy number
	5.3 Cut function and its approximation
		5.3.1 Error of approximation of [x]a, b by Sa, b(β)(x) for
	5.4 Approximation of piecewise linear membership function
	5.5 STP with unit transportation costs represented as fuzzy numbers
		5.5.1 Solution methodology
		5.5.2 A methodology using the concept minimum of fuzzy number
	5.6 Numerical example
		5.6.1 Solution using proposed methodology as in Section 5.1
		5.6.2 Solution using methodology as in Section 5.2
	5.7 Conclusion
	References
6 Profit maximization inventory model for non-instantaneous deteriorating items with imprecise costs
	6.1 Introduction
	6.2 Assumptions and notations
		6.2.1 Assumptions
		6.2.2 Notations
	6.3 Mathematical formulation
		6.3.1 Different inventory costs
		6.3.2 Sales revenue
		6.3.3 Profit function
		6.3.4 Defuzzification
	6.4 Solution procedure
	6.5 Numerical examples
	6.6 Sensitivity analysis
	6.7 Conclusion
	References
7 A fuzzy inventory model with permissible delay in payments for non-instantaneous deteriorating items under inflation
	7.1 Introduction
	7.2 Preliminaries
		7.2.1 Definition
		7.2.2 Definition
	7.3 Assumptions and notations
		7.3.1 Assumption
		7.3.2 Notation
	7.4 Mathematical model
		7.4.1 Fuzzy optimization model
	7.5 Numerical examples
		7.5.1 Crisp numerical example
		7.5.2 Fuzzy numerical example
	7.6 Conclusion
	References
8 Single- and multi-objective optimization problems with pentagonal fuzzy number
	8.1 Introduction
	8.2 Basic preliminaries
		8.2.1 Fuzzy set
		8.2.2 Fuzzy number
		8.2.3 α-cut of fuzzy number
		8.2.4 Pentagonal fuzzy number
		8.2.5 Signed-distance method
	8.3 Mathematical model
		8.3.1 Single-objective optimization model
		8.3.2 Multi-objective optimization model
	8.4 Methodology
		8.4.1 Crisp single-objective optimization model (CSOOM)
		8.4.2 Fuzzy single-objective optimization model (FSOOM)
		8.4.3 Crisp multi-objective optimization model (CMOOM)
		8.4.4 Weighted sum method (WSM)
		8.4.5 Fuzzy multi-objective optimization model (FMOOM)
	8.5 Numerical examples
	8.6 Conclusion
	References
9 Sensitivity analysis of fuzzy linear programming
	9.1 Introduction
	9.2 Preliminaries
	9.3 Examples
	9.4 Sensitivity analysis
		9.4.1 Variation in the requirement vector
		9.4.2 Variation in the cost vector
	9.5 Conclusion
	References
10 Constrained effective bit selection algorithm for solving 0–1 knapsack problem
	10.1 Introduction
	10.2 Description of knapsack 0–1
		10.2.1 Definition of greedy degree
	10.3 Dynamic expectation efficiency (DEE)
	10.4 Static expectation efficiency (SEE)
		10.4.1 Parallel computing
	10.5 Time complexity description
	10.6 Space complexity
	10.7 Experimental results and data analysis
		10.7.1 Simulation test
		10.7.2 Feasibility test
		10.7.3 Comparison among the algorithms
		10.7.4 Effectiveness test
		10.7.5 Stability test
	10.8 Conclusions and future work
	References
11 A transportation model with rough cost, demand, and supply
	11.1 Introduction
	11.2 Preliminaries
	11.3 Problem description
		11.3.1 Deterministic transportation model
		11.3.2 Uncertain transportation model
	11.4 Numerical example
	11.5 Conclusion
	References
12 Impact of COVID-19 on the world economy
	12.1 Introduction
		12.1.1 The primary financial issues looked at by rising economies
		12.1.2 The direct impact of NPIs
		12.1.3 Indirect impact of NPIs
		12.1.4 Commodity prices
		12.1.5 Existing influence represents an extra hazard
	12.2 Policy implication
		12.2.1 More gainful NPIs
	12.3 Conclusion
	References
13 Food waste: impact of COVID-19 on urban and rural areas
	13.1 Introduction
	13.2 Literature review
		13.2.1 Food waste behavior in the household
	13.3 Hypothesis formulation
	13.4 Research methodology
	13.5 Discussion
	13.6 Conclusion
	References
14 A conceptual study of association factors contributing to the stress level of parents during the pandemic era in NCR
	14.1 Introduction
	14.2 Review of literature
	14.3 Material and methods
	14.4 Data analysis
	14.5 Results and discussions
	References
Index