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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Carbon Emission,Green vehicle routing,bi-fuel light truck,soft time window,green logistics
- چکیده:
- چکیده انگلیسی: This paper formulates a mathematical model for the Green Vehicle Routing Problem (GVRP), incorporating bi-fuel (natural gas and gasoline) pickup trucks in a mixed vehicle fleet. The objective is to minimize overall costs relating to service (earliness and tardiness), transportation (fixed, variable and fuel), and carbon emissions. To reflect a real-world situation, the study considers: (1) a comprehensive fuel consumption function with a soft time window, and (2) an en-route fuel refueling option to eliminate the constraint of driving range. A linear set of valid inequalities for computing fuel consumption were introduced. In order to validate the presented model, first, the model is solved for an illustrative example. Then each component of cost objective function is considered separately so as to investigate the effects of each part on the obtained solutions and the importance of vehicles speed on transportation strategies. Computational analysis shows that, despite the limitation of an appropriate service infrastructure, the proposed model demonstrated an average reduction of 44%, 6% and 5% in carbon emission costs, total distribution costs, and transportation costs respectively. Moreover, the study found paradoxical effects of average speed, suggesting the need to manage trade-offs: while higher speeds reduced service costs, they increased carbon emission costs. In the next stage, some experiments modified from the literature are solved. According to these experiments, in all instances greater objective function values for Gasoline vehicles are gained. The difference in the carbon emission objective is also significant, with an average of 44.23% increase. Finally, managerial and institutional implications are discussed.
- انتشار مقاله: 31-03-1398
- نویسندگان: Neda Manavizadeh,Hamed Farrokhi-Asl,Stanley Frederick W.T. Lim
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Industrial and Systems Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Multi-objective optimization,time windows,Waste collection problem,interactive fuzzy programming,chance constraint programming
- چکیده:
- چکیده انگلیسی: This paper presents a novel multi-objective location arc-routing model in order to locate disposal facilities and to design optimal routes of residential waste taking into consideration many complicated real constraints such as a heterogeneous fleet of vehicles, time windows for customers, disposal facilities and the depot, capacities for vehicles and facilities. The first objective is the minimization of transportation costs, including service costs and fuel costs of vehicles. The second one minimizes total number of utilized vehicles. And finally, the third objective function is considered for minimizing total number of established disposal centers. Moreover, to come closer to reality the service time, amount of demands, capacities and cost parameters are considered as fuzzy ones. To solve the proposed model, a credibility-based fuzzy mathematical model and its interactive solution method with three recent approaches, are used and the results are compared with each other.
- انتشار مقاله: 31-01-1397
- نویسندگان: Masoud Rabani,Neda Manavizadeh,Abtin Boostani,Soroush Aghamohamadi
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Industrial and Systems Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Customer Satisfaction,Green supply chain,Fuzzy TOPSIS,Location routing inventory,backup strategy,multi objective gray wolf optimization algorithm
- چکیده:
- چکیده انگلیسی: This study introduces a green location, routing and inventory problem with customer satisfaction, backup distribution centers and risk of routes in the form of a non-linear mixed integer programming model. In this regard, time window is considered to increase the customer satisfaction of the model and transportation risks is taken into account for the reliability of the system. In addition, different factors are detected as the major factors affecting the risk of routs and a fuzzy TOPSIS method is applied to rank the related risk factors. Next, due to the complexity of the investigated model, two algorithms including multi-objective gray wolf optimization algorithms (MOGWO) and Non-Dominated Sorting Genetic algorithm (NSGA-II) are applied to solve the large-sized instances. The results prove the superiority of MOGWO in dealing with large-sized instances. In the next step, some sensitivity analysis is implemented on the model based on a case study andthe related results of case study are reported as well.
- انتشار مقاله: 26-05-1398
- نویسندگان: Neda Manavizadeh,Mahnaz Shaabani,Soroush Aghamohamadi
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Industrial and Systems Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Multi-objective location-routing,hazardous waste management,multi-objective model
- چکیده:
- چکیده انگلیسی: Industrial hazardous materials (hazmat) are byproduct of industrial production and include hazardous goods, such as flammable, toxic and corrosive materials that pose a risk to the environment.Hazardous waste management includes collection, transportation, treatment, recycling and disposal of industrial hazardous material in an organized manner. With the increasing industrialization of countries, the issue of waste management is more important than before. Therefore, the main purpose of this research is to optimize locations of recycling centers and routing hazardous. The methods used to solve the mathematical model include the ε-constraint method and the NSGA II algorithm.First, we examine the validation of proposed model. Then, the optimal values of the parameters of multi-objective meta-heuristic algorithm are determined by Taguchi approach and the proposed algorithms are used to solve the given problem for 19 examples with different sizes. Finally, two algorithms are compared based on the fiveidentified criteria. In addition, the run time for both methods was calculated and large-scale results were presented based on the multi-objective genetic algorithm. The results show the efficiencyofmulti-objective genetic algorithm in solving given problem, and in particular for problems with larger sizes.
- انتشار مقاله: 07-06-1396
- نویسندگان: Neda Manavizadeh,Iman Moayedi
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Backlogging,Robust optimization,Uncertainty in labor cost,Production Planning,Failure,Rework,particle swarm optimization,Uncertainty in demand
- چکیده:
- چکیده انگلیسی: In this paper, we consider a multi-site production planning problem subject to uncertainty in demand and workforce expenses. In our new mathematical model, we presented a production planning system considering failure in rework and breakdown. We also survey human workforce allocation and its expenses which are considered uncertain due to some tradeoff between company’s benefits and workforce union’s advantages. We presented a new robust particle swarm optimization to propose a model with the ability of handling uncertainties. Firstly, we apply the presented robust optimization to handle demand uncertainty separately, and then we extended our model to regard both uncertainties simultaneously. To show the practicability of the proposed algorithm, we solved a real problem in an industrial case study. We also analyzed the most important parameters in the presented robust model to find out which level of uncertainty has less constraint violation and determine the maximum budget of uncertainties that could be considered in the proposed model to expect acceptable optimal objective. The results showed that the proposed model can prepare a promising approach to fulfill an efficient production planning in a multi-site production planning.
- انتشار مقاله: 11-09-1391
- نویسندگان: Masoud Rabani,Nilufar Hosseini Aghozi,Neda Manavizadeh
- مشاهده