Issues

Journal & Issues

Volume 47 (2022): Issue 3 (September 2022)

Volume 47 (2022): Issue 2 (June 2022)

Volume 47 (2022): Issue 1 (February 2022)

Volume 46 (2021): Issue 4 (December 2021)

Volume 46 (2021): Issue 3 (September 2021)

Volume 46 (2021): Issue 2 (June 2021)

Volume 46 (2021): Issue 1 (March 2021)

Volume 45 (2020): Issue 4 (December 2020)

Volume 45 (2020): Issue 3 (September 2020)

Volume 45 (2020): Issue 2 (June 2020)

Volume 45 (2020): Issue 1 (March 2020)

Volume 44 (2019): Issue 4 (December 2019)

Volume 44 (2019): Issue 3 (September 2019)

Volume 44 (2019): Issue 2 (June 2019)

Volume 44 (2019): Issue 1 (March 2019)

Volume 43 (2018): Issue 4 (December 2018)

Volume 43 (2018): Issue 3 (September 2018)

Volume 43 (2018): Issue 2 (June 2018)

Volume 43 (2018): Issue 1 (March 2018)

Volume 42 (2017): Issue 4 (December 2017)

Volume 42 (2017): Issue 3 (September 2017)

Volume 42 (2017): Issue 2 (June 2017)

Volume 42 (2017): Issue 1 (February 2017)

Volume 41 (2016): Issue 4 (November 2016)

Volume 41 (2016): Issue 3 (September 2016)

Volume 41 (2016): Issue 2 (June 2016)

Volume 41 (2016): Issue 1 (March 2016)

Volume 40 (2015): Issue 4 (December 2015)

Volume 40 (2015): Issue 3 (September 2015)

Volume 40 (2015): Issue 2 (June 2015)

Volume 40 (2015): Issue 1 (March 2015)

Volume 39 (2014): Issue 4 (December 2014)

Volume 39 (2014): Issue 3 (September 2014)

Volume 39 (2014): Issue 2 (June 2014)

Volume 39 (2014): Issue 1 (February 2014)

Volume 38 (2013): Issue 4 (December 2013)

Volume 38 (2013): Issue 3 (September 2013)

Volume 38 (2013): Issue 2 (June 2013)

Volume 38 (2013): Issue 1 (March 2013)

Volume 37 (2012): Issue 4 (December 2012)

Volume 37 (2012): Issue 3 (September 2012)

Volume 37 (2012): Issue 2 (June 2012)

Volume 37 (2012): Issue 1 (March 2012)

Journal Details
Format
Journal
eISSN
2300-3405
First Published
24 Oct 2012
Publication timeframe
4 times per year
Languages
English

Search

Volume 47 (2022): Issue 2 (June 2022)

Journal Details
Format
Journal
eISSN
2300-3405
First Published
24 Oct 2012
Publication timeframe
4 times per year
Languages
English

Search

8 Articles
Open Access

Preface to the Special Issue on Computational Performance Analysis based on Novel Intelligent Methods: Exploration and Future Directions in Production and Logistics

Published Online: 09 Jul 2022
Page range: 107 - 110

Abstract

Abstract

This special issue of the Foundations of Computing and Decision Sciences, titled “Computational Performance Analysis based on Novel Intelligent Methods: Exploration and Future Directions in Production and Logistics”, is devoted to the application of Computational Performance Analysis (CPA) for real-life phenomena. The special issue and its editorial present novel intelligent methods as they meet with various research topics in production and logistics, especially in terms of challenges, limitations and future trends. This special issue aims to bring together current progress on the CPA, organization management, and novel models and solution techniques that can contribute to a better understanding of the CPA systems and delineate useful practical strategies. Methodologically interesting and well-documented case studies are highly recommended. Additionally, the special issue covers innovative cutting-edge research methodologies and applications in the related research field.

Open Access

Development of an Adaptive Genetic Algorithm to Optimize the Problem Of Unequal Facility Location

Published Online: 09 Jul 2022
Page range: 111 - 125

Abstract

Abstract

The problem of unequal facility location involves determining the location of a set of production equipment whose dimensions are different, as well as the interrelationships between each of them. This paper presents an efficient method for optimizing the problem of unequal facility layouts. In this method, the genetic algorithm is improved and developed into an adaptive genetic algorithm. In this algorithm, the mutation operator is applied only when the similarity of chromosomes in each population reaches a certain level. This intelligence prevents jumps in situations where they are not needed and reduces computational time. In order to measure the performance of the proposed algorithm, its performance is compared with the performance of conventional genetic algorithms and refrigeration simulators. Computational results show that the adaptive genetic algorithm is able to achieve higher-quality solutions.

Keywords

  • Unequal Facility location
  • Interactions
  • Adaptive Genetic Algorithm
  • Mutation Operator Intelligence
  • healthy lifestyle
Open Access

Developing a Mathematical Model for a Green Closed-Loop Supply Chain with a Multi-Objective Gray Wolf Optimization Algorithm

Published Online: 09 Jul 2022
Page range: 127 - 150

Abstract

Abstract

Intense competition in today’s market and quick change in customer preferences, along with the rapid development of technology and globalization, have forced companies to work as members of a supply chain instead of individual companies. The success of the supply chain depends on the integration and coordination of all its institutions to form an efficient network structure. An efficient network leads to cost savings throughout the supply chain and helps it respond to customer needs faster. Accordingly, and with respect to the importance of the supply chain, in this study a developed mathematical model for the design of a green closed-loop supply chain is presented. In this mathematical model, the economic and environmental objectives are simultaneously optimized. In order to tackle this mathematical model, two methods of epsilon constraint and multi-objective gray wolf optimization (MOGWO) algorithm have been applied. The results of comparisons between the two mentioned methods show that MOGWO reduce the average solving time from about 1300 seconds to 88 seconds. In the last step of this research, in order to show the application of the proposed mathematical model and the method of solving the research problem, it was implemented in the supply chain of Dalan Kouh diary product and the Pareto optimal solutions were analyzed.

Keywords

  • green closed-loop supply chain
  • epsilon constraint
  • multi-objective Gay wolf algorithm
  • Pareto boundary
Open Access

A New Model for Scheduling Operations in Modern Agricultural Processes

Published Online: 09 Jul 2022
Page range: 151 - 161

Abstract

Abstract

In recent years, the increase in population and the decrease in agricultural lands and water shortages have caused many problems for agriculture and farmers. That is why scheduling is so important for farmers. Therefore, the implementation of an optimal schedule will lead to better use of agricultural land, reduce water consumption in agriculture, increase efficiency and quality of agricultural products. In this research, a scheduling problem for harvesting agricultural products has been investigated. In this problem, there are n number of agricultural lands that in each land m agricultural operations are performed by a number of machines that have different characteristics. This problem is modeled as a scheduling problem in a flexible workshop flow environment that aims to minimize the maximum completion time of agricultural land. The problem is solved by programming an integer linear number using Gams software. The results show that the proposed mathematical model is only capable of solving small and medium-sized problems, and due to the Hard-NP nature of the problem, large-scale software is not able to achieve the optimal solution.

Keywords

  • Scheduling
  • Agricultural operations
  • Flexible workshop flow
  • Maximum completion time
Open Access

Design a Multi Period Closed-Loop Supply Chain Program to Supply Recycled Products

Published Online: 09 Jul 2022
Page range: 163 - 176

Abstract

Abstract

Over the course of the last decades, closed-loop supply chains (CLSC) and reverse logistics issues have attracted increasing attention owing to strict environmental laws, social responsibilities, economic interests, and customer awareness. Hence, the issue of closed-loop supply chain and reverse logistics has emerged as a field of research in the new era. This issue has received much attention because it allows recyclable products to return to their original cycle. Therefore, this study primarily intends to present a mathematical model for designing a supply chain network for recycled products. The multi-stage and multi-period objective function of the closed-loop supply chain is presented to meet that aim. In this chain, dismantling, recycling, and disposal centers are considered. The objective function is to reduce the total cost of the closed-loop supply chain. The results of optimizing the mathematical model demonstrate that this model has the necessary efficiency for use in recycled products.

Keywords

  • Closed-loop supply chain
  • Recycled products
  • Total cost reduction
  • Reverse logistics
Open Access

Optimizing the Multi-Level Location-Assignment Problem in Queue Networks Using a Multi-Objective Optimization Approach

Published Online: 09 Jul 2022
Page range: 177 - 192

Abstract

Abstract

Using hubs in distribution networks is an efficient approach. In this paper, a model for the location-allocation problem is designed within the framework of the queuing network in which services have several levels, and customers must go through these levels to complete the service. The purpose of the model is to locate an appropriate number of facilities among potential locations and allocate customers. The model is presented as a multi-objective nonlinear mixed-integer programming model. The objective functions include the summation of the customer and the waiting time in the system and the waiting time in the system and minimizing the maximum possibility of unemployment in the facility. To solve the model, the technique of accurate solution of the epsilon constraint method is used for multi-objective optimization, and Pareto solutions of the problem will be calculated. Moreover, the sensitivity analysis of the problem is performed, and the results demonstrate sensitivity to customer demand rate. Based on the results obtained, it can be concluded that the proposed model is able to greatly summate the customer and the waiting time in the system and reduce the maximum probability of unemployment at several levels of all facilities. The model can also be further developed by choosing vehicles for each customer.

Keywords

  • Location-Assignment
  • Hub
  • Reinforced Epsilon Constraint Method
  • Multilevel Services
  • Queue Theory
  • Multi-Objective Optimization
Open Access

Designing a Green Supply Chain Transportation System for an Automotive Company Based On Bi-Objective Optimization

Published Online: 09 Jul 2022
Page range: 193 - 207

Abstract

Abstract

Recently, due to the increasing awareness of communities regarding environmental issues and environmental regulations, companies have evolved to provide products with lower prices and better quality to retain and attract customers. Economics should also pay attention to environmental goals. Therefore, it is essential to provide a supply chain model that can consider both economic and environmental objectives. In this paper, the green direct supply chain network is presented to an automotive company, including five suppliers, primary warehouses, manufacturing plants, distributors, and sales centers. The objectives of this model are to minimize the total cost of construction, transportation, and the amount of carbon dioxide emissions during forwarding network transportation at all levels. The proposed model is also drawn using the weight method, which is one of the methods for solving multi-objective problems, and the solution of the model part. Ultimately, it has been discussed how much the automobile company should focus on reducing carbon dioxide so that managers can determine the best solutions from the Pareto border according to their organization’s priorities, which can be environmental or financial.

Keywords

  • Multi-Objective Optimization
  • Green Supply Chain
  • Transportation
  • Weighting Method
Open Access

The Main Trends and Challenges in The Development of the Different Industries During The COVID-19 Pandemic

Published Online: 09 Jul 2022
Page range: 209 - 231

Abstract

Abstract

The purpose of the research in this article is to investigate the main trends in the development of the different industries during the COVID-19 pandemic, to identify the main problems facing the different industries in the context of the global crisis, as well as to form the basic concepts necessary for a real recovery of the global industry. The authors identify the main problems facing the aviation industry in the developing world crisis and possible ways to solve them. As a working hypothesis, it is proposed to form the basic concepts necessary for preparing and implementing operational measures to restore passenger and cargo aviation. Considering the main threats facing the aviation industry during COVID-19, the article proposes the organizational and economic mechanisms to restore the industry. Furthermore, several recovery scenarios are considered, considering the relevant factors that have a particular impact. Next, a novel mathematical model for pharmaceutical products, which are the most important in COVID-19 pandemics, is proposed. Moreover, the model considers the uncertainty, and a robust optimization approach is applied. The study is based on a comprehensive analysis of documentary data provided by government agencies in several European countries. An analysis of global and Russian passenger traffic for Q1-Q4 (quartile) of 2020 and a development forecast for Q1-Q2 of 2021 is provided. The scenario problems facing the aviation industry in the context of the COVID-19 crisis are identified. There are key concepts necessary to prepare and implement effective measures to restore the aviation industry.

Keywords

  • Aviation industry
  • COVID-19
  • development trends
  • robust optimization
  • pharmaceutical industry
8 Articles
Open Access

Preface to the Special Issue on Computational Performance Analysis based on Novel Intelligent Methods: Exploration and Future Directions in Production and Logistics

Published Online: 09 Jul 2022
Page range: 107 - 110

Abstract

Abstract

This special issue of the Foundations of Computing and Decision Sciences, titled “Computational Performance Analysis based on Novel Intelligent Methods: Exploration and Future Directions in Production and Logistics”, is devoted to the application of Computational Performance Analysis (CPA) for real-life phenomena. The special issue and its editorial present novel intelligent methods as they meet with various research topics in production and logistics, especially in terms of challenges, limitations and future trends. This special issue aims to bring together current progress on the CPA, organization management, and novel models and solution techniques that can contribute to a better understanding of the CPA systems and delineate useful practical strategies. Methodologically interesting and well-documented case studies are highly recommended. Additionally, the special issue covers innovative cutting-edge research methodologies and applications in the related research field.

Open Access

Development of an Adaptive Genetic Algorithm to Optimize the Problem Of Unequal Facility Location

Published Online: 09 Jul 2022
Page range: 111 - 125

Abstract

Abstract

The problem of unequal facility location involves determining the location of a set of production equipment whose dimensions are different, as well as the interrelationships between each of them. This paper presents an efficient method for optimizing the problem of unequal facility layouts. In this method, the genetic algorithm is improved and developed into an adaptive genetic algorithm. In this algorithm, the mutation operator is applied only when the similarity of chromosomes in each population reaches a certain level. This intelligence prevents jumps in situations where they are not needed and reduces computational time. In order to measure the performance of the proposed algorithm, its performance is compared with the performance of conventional genetic algorithms and refrigeration simulators. Computational results show that the adaptive genetic algorithm is able to achieve higher-quality solutions.

Keywords

  • Unequal Facility location
  • Interactions
  • Adaptive Genetic Algorithm
  • Mutation Operator Intelligence
  • healthy lifestyle
Open Access

Developing a Mathematical Model for a Green Closed-Loop Supply Chain with a Multi-Objective Gray Wolf Optimization Algorithm

Published Online: 09 Jul 2022
Page range: 127 - 150

Abstract

Abstract

Intense competition in today’s market and quick change in customer preferences, along with the rapid development of technology and globalization, have forced companies to work as members of a supply chain instead of individual companies. The success of the supply chain depends on the integration and coordination of all its institutions to form an efficient network structure. An efficient network leads to cost savings throughout the supply chain and helps it respond to customer needs faster. Accordingly, and with respect to the importance of the supply chain, in this study a developed mathematical model for the design of a green closed-loop supply chain is presented. In this mathematical model, the economic and environmental objectives are simultaneously optimized. In order to tackle this mathematical model, two methods of epsilon constraint and multi-objective gray wolf optimization (MOGWO) algorithm have been applied. The results of comparisons between the two mentioned methods show that MOGWO reduce the average solving time from about 1300 seconds to 88 seconds. In the last step of this research, in order to show the application of the proposed mathematical model and the method of solving the research problem, it was implemented in the supply chain of Dalan Kouh diary product and the Pareto optimal solutions were analyzed.

Keywords

  • green closed-loop supply chain
  • epsilon constraint
  • multi-objective Gay wolf algorithm
  • Pareto boundary
Open Access

A New Model for Scheduling Operations in Modern Agricultural Processes

Published Online: 09 Jul 2022
Page range: 151 - 161

Abstract

Abstract

In recent years, the increase in population and the decrease in agricultural lands and water shortages have caused many problems for agriculture and farmers. That is why scheduling is so important for farmers. Therefore, the implementation of an optimal schedule will lead to better use of agricultural land, reduce water consumption in agriculture, increase efficiency and quality of agricultural products. In this research, a scheduling problem for harvesting agricultural products has been investigated. In this problem, there are n number of agricultural lands that in each land m agricultural operations are performed by a number of machines that have different characteristics. This problem is modeled as a scheduling problem in a flexible workshop flow environment that aims to minimize the maximum completion time of agricultural land. The problem is solved by programming an integer linear number using Gams software. The results show that the proposed mathematical model is only capable of solving small and medium-sized problems, and due to the Hard-NP nature of the problem, large-scale software is not able to achieve the optimal solution.

Keywords

  • Scheduling
  • Agricultural operations
  • Flexible workshop flow
  • Maximum completion time
Open Access

Design a Multi Period Closed-Loop Supply Chain Program to Supply Recycled Products

Published Online: 09 Jul 2022
Page range: 163 - 176

Abstract

Abstract

Over the course of the last decades, closed-loop supply chains (CLSC) and reverse logistics issues have attracted increasing attention owing to strict environmental laws, social responsibilities, economic interests, and customer awareness. Hence, the issue of closed-loop supply chain and reverse logistics has emerged as a field of research in the new era. This issue has received much attention because it allows recyclable products to return to their original cycle. Therefore, this study primarily intends to present a mathematical model for designing a supply chain network for recycled products. The multi-stage and multi-period objective function of the closed-loop supply chain is presented to meet that aim. In this chain, dismantling, recycling, and disposal centers are considered. The objective function is to reduce the total cost of the closed-loop supply chain. The results of optimizing the mathematical model demonstrate that this model has the necessary efficiency for use in recycled products.

Keywords

  • Closed-loop supply chain
  • Recycled products
  • Total cost reduction
  • Reverse logistics
Open Access

Optimizing the Multi-Level Location-Assignment Problem in Queue Networks Using a Multi-Objective Optimization Approach

Published Online: 09 Jul 2022
Page range: 177 - 192

Abstract

Abstract

Using hubs in distribution networks is an efficient approach. In this paper, a model for the location-allocation problem is designed within the framework of the queuing network in which services have several levels, and customers must go through these levels to complete the service. The purpose of the model is to locate an appropriate number of facilities among potential locations and allocate customers. The model is presented as a multi-objective nonlinear mixed-integer programming model. The objective functions include the summation of the customer and the waiting time in the system and the waiting time in the system and minimizing the maximum possibility of unemployment in the facility. To solve the model, the technique of accurate solution of the epsilon constraint method is used for multi-objective optimization, and Pareto solutions of the problem will be calculated. Moreover, the sensitivity analysis of the problem is performed, and the results demonstrate sensitivity to customer demand rate. Based on the results obtained, it can be concluded that the proposed model is able to greatly summate the customer and the waiting time in the system and reduce the maximum probability of unemployment at several levels of all facilities. The model can also be further developed by choosing vehicles for each customer.

Keywords

  • Location-Assignment
  • Hub
  • Reinforced Epsilon Constraint Method
  • Multilevel Services
  • Queue Theory
  • Multi-Objective Optimization
Open Access

Designing a Green Supply Chain Transportation System for an Automotive Company Based On Bi-Objective Optimization

Published Online: 09 Jul 2022
Page range: 193 - 207

Abstract

Abstract

Recently, due to the increasing awareness of communities regarding environmental issues and environmental regulations, companies have evolved to provide products with lower prices and better quality to retain and attract customers. Economics should also pay attention to environmental goals. Therefore, it is essential to provide a supply chain model that can consider both economic and environmental objectives. In this paper, the green direct supply chain network is presented to an automotive company, including five suppliers, primary warehouses, manufacturing plants, distributors, and sales centers. The objectives of this model are to minimize the total cost of construction, transportation, and the amount of carbon dioxide emissions during forwarding network transportation at all levels. The proposed model is also drawn using the weight method, which is one of the methods for solving multi-objective problems, and the solution of the model part. Ultimately, it has been discussed how much the automobile company should focus on reducing carbon dioxide so that managers can determine the best solutions from the Pareto border according to their organization’s priorities, which can be environmental or financial.

Keywords

  • Multi-Objective Optimization
  • Green Supply Chain
  • Transportation
  • Weighting Method
Open Access

The Main Trends and Challenges in The Development of the Different Industries During The COVID-19 Pandemic

Published Online: 09 Jul 2022
Page range: 209 - 231

Abstract

Abstract

The purpose of the research in this article is to investigate the main trends in the development of the different industries during the COVID-19 pandemic, to identify the main problems facing the different industries in the context of the global crisis, as well as to form the basic concepts necessary for a real recovery of the global industry. The authors identify the main problems facing the aviation industry in the developing world crisis and possible ways to solve them. As a working hypothesis, it is proposed to form the basic concepts necessary for preparing and implementing operational measures to restore passenger and cargo aviation. Considering the main threats facing the aviation industry during COVID-19, the article proposes the organizational and economic mechanisms to restore the industry. Furthermore, several recovery scenarios are considered, considering the relevant factors that have a particular impact. Next, a novel mathematical model for pharmaceutical products, which are the most important in COVID-19 pandemics, is proposed. Moreover, the model considers the uncertainty, and a robust optimization approach is applied. The study is based on a comprehensive analysis of documentary data provided by government agencies in several European countries. An analysis of global and Russian passenger traffic for Q1-Q4 (quartile) of 2020 and a development forecast for Q1-Q2 of 2021 is provided. The scenario problems facing the aviation industry in the context of the COVID-19 crisis are identified. There are key concepts necessary to prepare and implement effective measures to restore the aviation industry.

Keywords

  • Aviation industry
  • COVID-19
  • development trends
  • robust optimization
  • pharmaceutical industry

Plan your remote conference with Sciendo