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Article
Publication date: 1 October 2019

Hamed Farrokhi-Asl, Ahmad Makui, Roozbeh Ghousi and Masoud Rabbani

In recent years, governmental regulations and the pressure of non-governmental organizations have convinced corporations to consider sustainable issues in their decisions. A…

475

Abstract

Purpose

In recent years, governmental regulations and the pressure of non-governmental organizations have convinced corporations to consider sustainable issues in their decisions. A simultaneous design of forward and reverse logistics can keep us away from sub-optimality caused by tackling these two phases (forward and reverse logistics) separately.

Design/methodology/approach

Hence, this paper presents a new multi-objective mathematical model for integrated forward and reverse logistics regarding economic, environmental and social issues. A new hybrid multi-objective metaheuristic algorithm is developed to obtain a set of efficient solutions (Pareto solutions). The proposed algorithm hybridizes a well-known, non-dominated genetic algorithm (NSGA-II) with a simulated annealing algorithm.

Findings

To validate the algorithm, its results are compared to the obtained solutions from simple NSGA-II with respect to some comparison metrics. The numerical results show the efficiency of the proposed algorithm. Finally, concluding remarks and future research directions are provided.

Originality/value

By applying a model presented in this paper, one can reach to sustainable and integrated logistics network which considers forward and reverse flow of commodities simultaneously.

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Article
Publication date: 25 February 2020

Masoud Rabbani, Parisa Hashemi, Pegah Bineshpour and Hamed Farrokhi-Asl

The purpose of this study is twofold: first, to examine the role of non-governmental organizations (NGOs) in increasing customer environmental awareness (CEA) to decrease the…

302

Abstract

Purpose

The purpose of this study is twofold: first, to examine the role of non-governmental organizations (NGOs) in increasing customer environmental awareness (CEA) to decrease the municipal solid waste (MSW), and secondly, to examine the effect of government policies in the amount of air pollution caused by transfer stations (TSs).

Design/methodology/approach

This study proposes a mixed-integer nonlinear programming model. For solving this multi-objective problem, the authors use epsilon constraint method, which presented eight Pareto solutions. For selecting the best solution, the analytic hierarchy process approach is used. The presented model is applied on a real case study, and the results are discussed and sensitivity analysis is implemented on the parameters of the concern.

Findings

This study confirms the assumption that by allocating budget to NGOs for increasing CEA, the produced waste will be decreased.

Research limitations/implications

In the present study, the authors only investigate air pollution caused by TS. Future studies can investigate other types of pollution. Furthermore, uncertainty in the amount of produced waste can be variable making the problem closer to the real environment. In this case, robust optimization may have better results.

Practical implications

Based on the results of sensitivity analysis, some implications obtain that can highlight by managers in the decision-making process. The operational costs of TS have a critical aspect in founding TS, so using new technology and high-tech machines for operational processes of TSs, can result in decreasing the running cost of TSs. Also, the determination of TS capacity is a remarkable issue in optimization, which should be paid special attention to this for the design of TSs in the planning phase of the system. Moreover, collaborating with NGOs has a good effect on increasing CEA that results in a decrease of MSW.

Originality/value

The role of NGOs and government simultaneity has been considered in a green supply chain. Moreover, the authors considered TS between source and disposal that reduce the time of transferring waste. Therefore, this study can be beneficial for the MSW management system, which faces the problems in the lack of capacity and transportation problems and environmental issues by proposing solutions in three studies including economic, environmental and social aspects.

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Article
Publication date: 17 September 2018

Masoud Rabbani, Pooya Pourreza, Hamed Farrokhi-Asl and Narjes Nouri

This paper, considers the multi-depot vehicle routing problem with time window considering two repair and pickup vehicles (CMDVRPTW).

426

Abstract

Purpose

This paper, considers the multi-depot vehicle routing problem with time window considering two repair and pickup vehicles (CMDVRPTW).

Design/methodology/approach

The objective of this problem is minimization of the total traveling cost and the time window violations. Two meta-heuristic algorithms, namely, simple genetic algorithm (GA) and hybrid genetic algorithm (HGA) are used to find the best solution for this problem. A comparison on the results of these two algorithms has been done and based on the outcome, it has been proved that HGA has better performance than GA.

Findings

A comparison on the results of these two algorithms has been done and based on the outcome, it has been proved that HGA has better performance than GA.

Originality/value

This paper, considers the multi-depot vehicle routing problem with time window considering two repair and pickup vehicles (CMDVRPTW). The defined problem is a practical problem in the supply management and logistic. The repair vehicle services the customers who have goods, while the pickup vehicle visits the customer with nonrepaired goods. All the vehicles belong to an internal fleet of a company and have different capacities and fixed/variable cost. Moreover, vehicles have different limitations in their time of traveling. The objective of this problem is minimization of the total traveling cost and the time window violations. Two meta-heuristic algorithms (simple genetic algorithm and hybrid one) are used to find the best solution for this problem.

Details

Journal of Modelling in Management, vol. 13 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

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Article
Publication date: 18 August 2021

Masoud Rabbani, Soroush Aghamohamadi Bosjin, Neda Manavizadeh and Hamed Farrokhi-Asl

This paper aims to present a novel bi-objective mathematical model for a production-inventory system under uncertainty.

136

Abstract

Purpose

This paper aims to present a novel bi-objective mathematical model for a production-inventory system under uncertainty.

Design/methodology/approach

This paper addresses agile and lean manufacturing concepts alongside with green production methods to design an integrated capacitated lot sizing problem (CLSP). From a methodological perspective, the problem is solved in three phases. In the first step, an FM/M/C queuing system is used to minimize the number of customers waited to receive their orders. In the second step, an effective approach is applied to deal with the fuzzy bi-objective model and finally, a hybrid metaheuristic algorithm is used to solve the problem.

Findings

Some numerical test problems and sensitivity analyzes are conducted to measure the efficiency of the proposed model and the solution method. The results validate the model and the performance of the solution method compared to Gams results in small size test problems and prove the superiority of the hybrid algorithm in comparison with the other well-known metaheuristic algorithms in large size test problems.

Originality/value

This paper presents a novel bi-objective mathematical model for a CLSP under uncertainty. The proposed model is conducted on a practical case and several sensitivity analysis are conducted to assess the behavior of the model. Using a queue system, this problem aims to reduce the items waited in the queue to receive service. Two objective functions are considered to maximize the profit and minimize the negative environmental effects. In this regard, the second objective function aims to reduce the amount of emitted carbon.

Details

Journal of Modelling in Management, vol. 17 no. 4
Type: Research Article
ISSN: 1746-5664

Keywords

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Article
Publication date: 27 November 2024

Milad Shahvaroughi Farahani, Shiva Babaei, Zahra Sadat Kharazan, Ali Bai, Zahra Rahmati, Ghazal Ghasemi, Fardin Alipour and Hamed Farrokhi-Asl

This paper aims to predict Dogecoin price by using artificial intelligence (AI) methods and comparing the results with the econometrics models.

17

Abstract

Purpose

This paper aims to predict Dogecoin price by using artificial intelligence (AI) methods and comparing the results with the econometrics models.

Design/methodology/approach

An artificial neural network (ANN) was applied as a prediction method without any optimization techniques. Additionally, the genetic algorithm (GA) is used to select the most appropriate input variables. Additionally, based on the literature review and the relationships between crypto-price and global indices, 20 economic indicators, such as Coinbase Bitcoin, Coinbase Litecoin and US dollars, along with main global stock indices such as FTSE100 and NIFTY50, are identified as input variables for the model. Lichtenberg algorithm (LA) and aquila optimization (AO) algorithm are used to make the ANN more robust. To validate our algorithms, they have been implemented on daily data for the last three years. To demonstrate the superiority of the models over traditional methods such as econometrics, regression analysis and curve fitting techniques are used. The effectiveness of these models is then evaluated and compared using criteria such as recall, accuracy and precision.

Findings

The results indicate that AI-based algorithms not only enhance the accuracy, recall and precision of calculations but also expedite the process without requiring the numerous and restrictive assumptions associated with time series and econometric models.

Originality/value

The main contribution of this paper is the application of novel approaches such as AO and LA to improve the predictive capabilities of the ANN method for various cryptocurrencies’ prices. It demonstrates the superiority of the proposed algorithms over traditional econometric models using real-life data.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

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