American Journal of Operations Research

Journal Information
ISSN / EISSN : 2160-8830 / 2160-8849
Published by: Scientific Research Publishing, Inc. (10.4236)
Total articles ≅ 396
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Ukamaka Cynthia Orumie, Egenti Francis Nzerem, Chekwube Bartholomew Desmond
American Journal of Operations Research, Volume 12, pp 94-110; https://doi.org/10.4236/ajor.2022.123006

Abstract:
In this paper, a fish farm was modeled using the Lexicographic linear goal programming approach due to incommensurability in objectives. The study considered the fish farming plan with two sizes of catfish from stocking to harvesting at four-month intervals. The multi-objective goals developed are required raw materials feed, water, light (resource utilization), sales revenue, profit realized, labor utilization, production costs, and pond utilization. The developed model was tested using related data collected from the farm records with the use of TORA 2007 software. The compromised solution from the results showed that the developed model is an efficient tool for decision-making process in the fish farm business organization.
Shoichiro Miyamoto, Yoshinobu Tamura, Shigeru Yamada
American Journal of Operations Research, Volume 12, pp 111-125; https://doi.org/10.4236/ajor.2022.123007

Abstract:
Recently, many open source software (OSS) developed by various OSS projects. Also, the reliability assessment methods of OSS have been proposed by several researchers. Many methods for software reliability assessment have been proposed by software reliability growth models. Moreover, our research group has been proposed the method of reliability assessment for the OSS. Many OSS use bug tracking system (BTS) to manage software faults after it released. It keeps a detailed record of the environment in terms of the faults. There are several methods of reliability assessment based on deep learning for OSS fault data in the past. On the other hand, the data registered in BTS differences depending on OSS projects. Also, some projects have the specific collection data. The BTS has the specific collection data for each project. We focus on the recorded data. Moreover, we investigate the difference between the general data and the specific one for the estimation of OSS reliability. As a result, we show that the reliability estimation results by using specific data are better than the method using general data. Then, we show the characteristics between the specified data and general one in this paper. We also develop the GUI-based software to perform these reliability analyses so that even those who are not familiar with deep learning implementations can perform reliability analyses of OSS.
Nickson Nagaaba
American Journal of Operations Research, Volume 12, pp 127-155; https://doi.org/10.4236/ajor.2022.124008

Abstract:
Purpose: Leagile manufacturing is one of the time-based manufacturing practices used to improve factory performance. It is a practice that combines initiatives of Lean and agile manufacturing under certain enabling competences. Therefore, the purpose of this study is investigate the combinative nature of time-based manufacturing practices under unique enabling competences and their impact on performance of factories in Uganda. Methodology: Firstly, the underlying factor structure of competences and time-based manufacturing was examined was conducted using Principal Component Analysis (PCA). Enabling competences and time-base manufacturing practices were modelled and validated for each using confirmatory factor analysis, particularly composite reliability, average variance extracted and convergent validity. A fully fledged structural equation model was used to test the impact of leagile manufacturing on performance of factories. Findings: The study results revealed that time-based manufacturing of lean, and leagile are related but differ, in terms of their enabling competences and philosophical orientation. The findings also revealed that when small and medium factories in Uganda adopt leagile practice, they are likely not improve their performance. This is perhaps due to the fact that small and medium factories have inadequate resources. Practical Implications: The study findings shed more insights on the factors that enable adoption and implementation of time-based manufacturing practices. The extent to which these competences are orchestrated determines the benefits derived from the time-based manufacturing practices. In addition, small and medium enterprises should keenly make a choice on the appropriate practices that purposely reduce their lead time and cost of conversion. Originality: This study investigated the combinative nature of time-based manufacturing practices under unique enabling competences and their impact on performance of factories in Uganda. It is among the few studies that provide evidence on the leagile model anchored in the appropriate enabling competences in the context of developing countries. The empirical survey was done on small and medium factories to validate a leagile manufacturing model and tested its impact on factory performance.
Sukriti Gangwar, Chandra Sen
American Journal of Operations Research, Volume 12, pp 11-17; https://doi.org/10.4236/ajor.2022.121002

Abstract:
Multi-goal and multi-objective optimizations are similar techniques to achieve multiple conflicting goals/objectives simultaneously. There are several techniques for solving multi-goal and multi-objective optimization problems. The present study proposed the possibility of convertibility in solving multi-goal and multi-objective optimization problems.
Taku Yanagisawa, Yoshinobu Tamura, Adarsh Anand, Shigeru Yamada
American Journal of Operations Research, Volume 12, pp 1-10; https://doi.org/10.4236/ajor.2022.121001

Abstract:
The software reliability model is the stochastic model to measure the software reliability quantitatively. A Hazard-Rate Model is the well-known one as the typical software reliability model. We propose Hazard-Rate Models Considering Fault Severity Levels (CFSL) for Open Source Software (OSS). The purpose of this research is to make the Hazard-Rate Model considering CFSL adapt to baseline hazard function and 2 kinds of faults data in Bug Tracking System (BTS), i.e., we use the covariate vectors in Cox proportional Hazard-Rate Model. Also, we show the numerical examples by evaluating the performance of our proposed model. As the result, we compare the performance of our model with the Hazard-Rate Model CFSL.
Media A. Omer, Nejmaddin A. Sulaiman
American Journal of Operations Research, Volume 12, pp 83-93; https://doi.org/10.4236/ajor.2022.123005

Abstract:
In this paper, a cubic objective programming problem (COPP) is defined. Introduced a new modification to solve a cubic objective programming problem. Suggested an algorithm for its solution. Also reported the algorithm of the usual simplex method. Application talks about how the developed algorithm can be used to unravel non-linear. The proposed technique, modification simplex technique, can be used with the constructed numerical examples an illustrative numerical problems are given to demonstrate the algorithms.
Mint Elhassen Emani, Amadou Coulibaly, Salimata G. Diagne, Ahmedou Ould Haouba, Alain Ngoma Mby
American Journal of Operations Research, Volume 12, pp 64-81; https://doi.org/10.4236/ajor.2022.122004

Abstract:
In this paper, the map of a network of air routes was updated by removing the non-optimal routes and replacing them with the best ones. An integer linear programming model was developed. The aim was to find optimal routes in superspace based on performance-based navigation. The optimal routes were found from a DIJKSTRA algorithm that calculates the shortest path in a graph. Simulations with python language on real traffic areas showed the improvements brought by surface navigation. In this work, the conceptual phase and the upper airspace were studied.
Bruno G. Rüttimann, Martin T. Stöckli
American Journal of Operations Research, Volume 12, pp 19-63; https://doi.org/10.4236/ajor.2022.122003

Abstract:
The recently experienced hype concerning the so-called “4th Industrial Revolution” of production systems has prompted several papers of various subtopics regarding Cyber-Phdysical Production Systems (CPPS). However, important aspects such as the modelling of CPPS to understand the theory regarding the performance of highly non-ergodic and non-deterministic flexible manufacturing systems in terms of Exit Rate (ER), Manufacturing Lead Time (MLT), and On-Time Delivery (OTD) have not yet been examined systematically and even less modeled analytically. To develop the topic, in this paper, the prerequisites for modelling such systems are defined in order to be able to derive an explicit and dedicated production mathematics-based understanding of CPPS and its dynamics: switching from explorative simulation to rational modelling of the manufacturing “physics” led to an own and specific manufacturing theory. The findings have led to enouncing, among others, the Theorem of Non-Ergodicity as well as the Batch Cycle Time Deviation Function giving important insights to model digital twin-based CPPS for complying with the mandatory OTD.
Vincenth Udok Udeme, Ukamaka Cynthia Orumie
American Journal of Operations Research, Volume 11, pp 181-198; https://doi.org/10.4236/ajor.2021.113011

Abstract:
The purpose of this work is to apply Game theory approach to determine patients’ preferences of healthcare facilities for quality healthcare in Akwa Ibom State. Cross-sectional descriptive study and purposive sampling technique were adopted in order to collect the relevant data. Factors influencing patients’ preferences of health care facilities between public and private hospitals in Akwa Ibom State were assessed using a set of questionnaires which were distributed to 9976 patients in University of Uyo Teaching Hospital, Uyo, Akwa Ibom State. A two-person zero sum game theory approach was applied. Perception of quality healthcare services received by respondent’s preferred facilities between public and private hospitals was examined. Also the reasons for patients’ persistence of their preferred facilities were evaluated using questionnaire. The optimal strategy and the value of the game were determined using the factors influencing patients’ preferences of healthcare facilities, and analysed with two-person-zero-sum game. Facility that gives their clients the best satisfaction was identified. The data collected through questionnaire were analysed using the rules of dominance in a two-person-zero-sum game and TORA statistical software was employed. The result shows that the value of the game, v = 330 which implies that the game is favourable to public hospital. The result also showed that patients preferred public hospitals due to costs of services with probability one (1), while private hospitals attributed their preferences to attitude of healthcare providers with probability one (1).
Jamil Uddin, Shirajul Islam Ukil, Aminur Rahman Khan, Sharif Uddin
American Journal of Operations Research, Volume 11, pp 1-14; https://doi.org/10.4236/ajor.2021.111001

Abstract:
This paper considers a model regarding the products with finite life which allows defective items in reproduction and causes a small amount of decay. The market demand is assumed to be level dependent linear type. The model has also considered the constant production rate which stops after a desired level of inventories and that is the highest level of it. Due to the market demand, defective item and product’s decay, the inventory reduces to the zero level where again the production cycle starts. With a numerical search procedure, the proof of the proposed model has been shown. The objective of the proposed model is to find out the total optimum inventory cost, optimum ordering cost and optimum ordering cycle.
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