Most recent issue published online in the International Journal of Mathematics in Operational Research.
International Journal of Mathematics in Operational Research
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International Journal of Mathematics in Operational Research
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http://www.inderscience.com/browse/index.php?journalID=320&year=2024&vol=27&issue=2
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An EOQ inventory policy varying with exponential-constant-exponential demand and shortages
http://www.inderscience.com/link.php?id=137037
In real market situations, it is often seen that most demands of the seasonal commodities run through three different phases, e.g., growth, steady and decline. The demand and the deterioration are taken as exponential-constant-exponential functions of time and constant, respectively. The model is divided into three policies according to the occurrence of the shortages period. The main purpose of the present paper is to investigate the effect of exponential-constant-exponential demand with seasonal commodities within the economic order quantity (EOQ) framework. Shortages as well as complete backlogged demand have been taken into consideration. A simple analytical procedure is presented to compute the optimal solutions of each policy. The model is well-explained with the help of three numerical examples. Finally, sensitivity analyses of all examples have also been performed to study the effectiveness of several system parameters on optimal solutions.
An EOQ inventory policy varying with exponential-constant-exponential demand and shortages
Itishree Rout; Trailokyanath Singh; Ameeya Kumar Nayak
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 145 - 166
In real market situations, it is often seen that most demands of the seasonal commodities run through three different phases, e.g., growth, steady and decline. The demand and the deterioration are taken as exponential-constant-exponential functions of time and constant, respectively. The model is divided into three policies according to the occurrence of the shortages period. The main purpose of the present paper is to investigate the effect of exponential-constant-exponential demand with seasonal commodities within the economic order quantity (EOQ) framework. Shortages as well as complete backlogged demand have been taken into consideration. A simple analytical procedure is presented to compute the optimal solutions of each policy. The model is well-explained with the help of three numerical examples. Finally, sensitivity analyses of all examples have also been performed to study the effectiveness of several system parameters on optimal solutions.]]>
10.1504/IJMOR.2024.137037
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 145 - 166
Itishree Rout
Trailokyanath Singh
Ameeya Kumar Nayak
Department of Mathematics, C.V. Raman Global University, Bhubaneswar †752054, India ' Department of Mathematics, C.V. Raman Global University, Bhubaneswar †752054, India ' Department of Mathematics, IIT Roorkee, Roorkee 247667, India
backlogging
deterioration
economic order quantity
EOQ
exponential-constant-exponential type
replenishment
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Multi-objective perishable multi-item green inventory models with uncertain finite time horizons and constraints by neutrosophic optimisation approach
http://www.inderscience.com/link.php?id=137053
The business period of seasonal products, such as mango, broccoli, etc., is finite over the years due to their availability, which is again uncertain for seasonal variations. According to FAO, about 40% of India's fruits and vegetables perish before reaching consumers. Due to global warming, firms have incorporated carbon management into business decisions. The resources in business are always limited and uncertain. Considering these facts, multi-objective perishable multi-product EOQ models with stock-dependent demand are formulated under crisp, uncertain (fuzzy, random, rough and neutrosophic) time horizons and constraints. The objective is to maximise total profit while minimising wastage costs and carbon emissions. Proposed models are solved using neutrosophic optimisation approach. The multi-objective problems are transformed into single ones using the weighted-sum method and solved through GRG (LINGO 11.0) method. Models are illustrated with numerical examples, and some sensitivity analyses are presented. A trade-off between profit and carbon emission is depicted.
Multi-objective perishable multi-item green inventory models with uncertain finite time horizons and constraints by neutrosophic optimisation approach
Chaitali Kar; Manoranjan De; Manoranjan Maiti; Pritha Das
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 167 - 198
The business period of seasonal products, such as mango, broccoli, etc., is finite over the years due to their availability, which is again uncertain for seasonal variations. According to FAO, about 40% of India's fruits and vegetables perish before reaching consumers. Due to global warming, firms have incorporated carbon management into business decisions. The resources in business are always limited and uncertain. Considering these facts, multi-objective perishable multi-product EOQ models with stock-dependent demand are formulated under crisp, uncertain (fuzzy, random, rough and neutrosophic) time horizons and constraints. The objective is to maximise total profit while minimising wastage costs and carbon emissions. Proposed models are solved using neutrosophic optimisation approach. The multi-objective problems are transformed into single ones using the weighted-sum method and solved through GRG (LINGO 11.0) method. Models are illustrated with numerical examples, and some sensitivity analyses are presented. A trade-off between profit and carbon emission is depicted.]]>
10.1504/IJMOR.2024.137053
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 167 - 198
Chaitali Kar
Manoranjan De
Manoranjan Maiti
Pritha Das
Department of Mathematics, Indian Institute of Engineering Science and Technology, Howrah-711103, West Bengal, India ' Department of Mathematics, Mugberia Gangadhar Mahavidyalaya, Purba Medinipur-721425, West Bengal, India ' Department of Applied Mathematics, Vidyasagar University, Paschim Medinipur-721102, West Bengal, India ' Department of Mathematics, Indian Institute of Engineering Science and Technology, Howrah-711103, West Bengal, India
inventory
seasonal products
uncertain time horizon
carbon emission
neutrosophic optimisation
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Copyright © 2024 Inderscience Enterprises Ltd.
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198
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New population-based simple algorithms for solving global optimisation problems
http://www.inderscience.com/link.php?id=137039
Heuristic algorithms have effectively been used for solving global optimisation problems in a continuous space. It can be applied to both constrained and unconstrained problems. Presently, several population-based algorithms were proposed by researchers and are available in the literature but those are not enough to solve the issues. Therefore, this study has proposed five new population-based simple algorithms that do not require any tuning parameter. A different strategy was used for updating the solution set. Unlike other algorithms, the solution set is constructed using three or four expressions to ensure an effective search and move towards the optimal/near-optimal solution. Each expression is used to build the population partially and the best one is selected for the next iteration. Further, it is compared with the recent popular arithmetic optimisation algorithm (AOA) using different benchmark functions and test suites of CEC2019. The dimensions are varied from 2 to 1,000. The results demonstrate the better performance of new algorithms over AOA. However, five real-world problems with constraints are also analysed to further validate their efficacy.
New population-based simple algorithms for solving global optimisation problems
A. Baskar; M.A. Sai Balaji; Jitendra Kumar Katiyar; Bharti Nagpal; J. Rajesh Babu
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 199 - 222
Heuristic algorithms have effectively been used for solving global optimisation problems in a continuous space. It can be applied to both constrained and unconstrained problems. Presently, several population-based algorithms were proposed by researchers and are available in the literature but those are not enough to solve the issues. Therefore, this study has proposed five new population-based simple algorithms that do not require any tuning parameter. A different strategy was used for updating the solution set. Unlike other algorithms, the solution set is constructed using three or four expressions to ensure an effective search and move towards the optimal/near-optimal solution. Each expression is used to build the population partially and the best one is selected for the next iteration. Further, it is compared with the recent popular arithmetic optimisation algorithm (AOA) using different benchmark functions and test suites of CEC2019. The dimensions are varied from 2 to 1,000. The results demonstrate the better performance of new algorithms over AOA. However, five real-world problems with constraints are also analysed to further validate their efficacy.]]>
10.1504/IJMOR.2024.137039
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 199 - 222
A. Baskar
M.A. Sai Balaji
Jitendra Kumar Katiyar
Bharti Nagpal
J. Rajesh Babu
Panimalar Institute of Technology, Chennai, India ' BSA Crescent Institute of Science and Technology, Chennai, India ' SRM Institute of Science and Technology, Chennai, India ' NSUT East Campus, New Delhi, India ' K.L.N. College of Engineering, Tamil Nadu, India
population-based
benchmark function
arithmetic optimisation algorithm
AOA
trigonometric algorithm
constrained optimisation
unconstrained optimisation
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Aspiration level-based non-dominated sorting genetic algorithm-II and III for multi-objective shortest path problem in a trapezoidal environment
http://www.inderscience.com/link.php?id=137054
The present article provides aspiration level (AL)-based non-dominated sorting genetic algorithm (NSGA)-II and AL-based NSGA-III utilising an exponential membership function (EMF) with possibility distribution to tackle fuzzy multi-objective shortest path problem (FMOSPP). In this study, fuzzy judgement for trapezoidal fuzzy number is classified for the decision-maker (DM) to optimise fuzzy objective function scenarios like optimistic, most likely lower, most likely upper, and pessimistic at the same time, utilising <i>α</i>-level sets. A numerical demonstration and a dataset have been offered to portray the application of the recommended methodologies. This study suggests that AL-based NSGA-II and AL-based NSGA-III can handle FMOSPP effectively and efficiently with optimal outputs. These methods provide solutions as per DM's AL. Thus it is very effective to manage real-world multi-objective shortest path problems (MOSPPs).
Aspiration level-based non-dominated sorting genetic algorithm-II and III for multi-objective shortest path problem in a trapezoidal environment
Aniket Todkar; Jayesh M. Dhodiya
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 223 - 253
The present article provides aspiration level (AL)-based non-dominated sorting genetic algorithm (NSGA)-II and AL-based NSGA-III utilising an exponential membership function (EMF) with possibility distribution to tackle fuzzy multi-objective shortest path problem (FMOSPP). In this study, fuzzy judgement for trapezoidal fuzzy number is classified for the decision-maker (DM) to optimise fuzzy objective function scenarios like optimistic, most likely lower, most likely upper, and pessimistic at the same time, utilising <i>α</i>-level sets. A numerical demonstration and a dataset have been offered to portray the application of the recommended methodologies. This study suggests that AL-based NSGA-II and AL-based NSGA-III can handle FMOSPP effectively and efficiently with optimal outputs. These methods provide solutions as per DM's AL. Thus it is very effective to manage real-world multi-objective shortest path problems (MOSPPs).]]>
10.1504/IJMOR.2024.137054
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 223 - 253
Aniket Todkar
Jayesh M. Dhodiya
Department of Mathematics and Humanities, SV National Institute of Technology, Surat, Gujrat, India ' Department of Mathematics and Humanities, SV National Institute of Technology, Surat, Gujrat, India
multi-objective shortest path problem
MOSPP
aspiration level
exponential membership function
EMF
α-level set
trapezoidal fuzzy number
genetic algorithm
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Optimal server analysis of M/M/c queueing model to reduce the waiting time of patients in healthcare service
http://www.inderscience.com/link.php?id=137041
Queueing system is a mathematical design known to be the theory of overcrowding. Healthcare organisation is one of the applications for queueing theory. This paper provides about the healthcare setting at the Arathana ortho local hospital at Pollachi. The proposed queuing model has used the multi-server system with a first come, first server queue discipline. The arrival rate follows Poisson distribution and service rate follows an exponential distribution. The actual data were collected in the ortho hospital and examined using the windows-based TORA optimisation technique. Performance measures and optimal number of servers were found. The result shows that the optimal server to serve the patients and also to reduce the waiting time of patients. The technique is manageable to utilise in the hospital.
Optimal server analysis of M/M/c queueing model to reduce the waiting time of patients in healthcare service
K. Preethi Sowndharya; J. Ebenesar Anna Bagyam
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 254 - 266
Queueing system is a mathematical design known to be the theory of overcrowding. Healthcare organisation is one of the applications for queueing theory. This paper provides about the healthcare setting at the Arathana ortho local hospital at Pollachi. The proposed queuing model has used the multi-server system with a first come, first server queue discipline. The arrival rate follows Poisson distribution and service rate follows an exponential distribution. The actual data were collected in the ortho hospital and examined using the windows-based TORA optimisation technique. Performance measures and optimal number of servers were found. The result shows that the optimal server to serve the patients and also to reduce the waiting time of patients. The technique is manageable to utilise in the hospital.]]>
10.1504/IJMOR.2024.137041
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 254 - 266
K. Preethi Sowndharya
J. Ebenesar Anna Bagyam
Department of Mathematics, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India ' Department of Mathematics, Karpagam Academy of Higher Education, Coimbatore 641021, India; Department of Mathematics, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India
service cost
patients waiting time cost
optimal server level
service time
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Mean time to failure modelling and sensitivity analysis of mixed standby serial systems
http://www.inderscience.com/link.php?id=137043
In this article, we investigate and compare the mean time to failure (MTTF) of series-parallel systems. This paper considers four different configurations with each having exponential failure and repair time. Each configuration consisting of the main, warm and cold standby units. A cold standby unit is included in Configuration 1 together with two warm standby units. Two cold standby units and one warm standby unit make up Configuration 2. In Configuration 3, there are four primary units, two warm standby units, and one cold standby unit. The Configuration 4 consists of six primary units, one warm standby unit, and two cold standby units. First order linear differential difference equations are used to produce a mathematical formula for MTTF for each configuration, which is then verified through analytical and numerical testing. Through the analytical and ranking experiment, Configuration 1 is found to be optimal.
Mean time to failure modelling and sensitivity analysis of mixed standby serial systems
Ibrahim Yusuf; Muhammad Sagir Aliyu; Mus'abu Musa
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 267 - 289
In this article, we investigate and compare the mean time to failure (MTTF) of series-parallel systems. This paper considers four different configurations with each having exponential failure and repair time. Each configuration consisting of the main, warm and cold standby units. A cold standby unit is included in Configuration 1 together with two warm standby units. Two cold standby units and one warm standby unit make up Configuration 2. In Configuration 3, there are four primary units, two warm standby units, and one cold standby unit. The Configuration 4 consists of six primary units, one warm standby unit, and two cold standby units. First order linear differential difference equations are used to produce a mathematical formula for MTTF for each configuration, which is then verified through analytical and numerical testing. Through the analytical and ranking experiment, Configuration 1 is found to be optimal.]]>
10.1504/IJMOR.2024.137043
International Journal of Mathematics in Operational Research, Vol. 27, No. 2 (2024) pp. 267 - 289
Ibrahim Yusuf
Muhammad Sagir Aliyu
Mus'abu Musa
Department of Mathematical Sciences, Bayero University, Kano, Nigeria ' Department of Mathematics, Jigawa State College of Education, Gumel, Nigeria ' Department of Mathematics, Faculty of Physical Sciences, Kebbi State University of Science and Technology, Aliero, Kebbi State, Nigeria
mean time to failure
MTTF
mixed standby
redundancy
series-parallel
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