16,727 research outputs found
Robust Multi-Objective Sustainable Reverse Supply Chain Planning: An Application in the Steel Industry
In the design of the supply chain, the use of the returned products and their recycling in the production and consumption network is called reverse logistics. The proposed model aims to optimize the flow of materials in the supply chain network (SCN), and determine the amount and location of facilities and the planning of transportation in conditions of demand uncertainty. Thus, maximizing the total profit of operation, minimizing adverse environmental effects, and maximizing customer and supplier service levels have been considered as the main objectives. Accordingly, finding symmetry (balance) among the profit of operation, the environmental effects and customer and supplier service levels is considered in this research. To deal with the uncertainty of the model, scenario-based robust planning is employed alongside a meta-heuristic algorithm (NSGA-II) to solve the model with actual data from a case study of the steel industry in Iran. The results obtained from the model, solving and validating, compared with actual data indicated that the model could optimize the objectives seamlessly and determine the amount and location of the necessary facilities for the steel industry more appropriately.This article belongs to the Special Issue Uncertain Multi-Criteria Optimization Problem
Fixed-Charge Solid Transportation Problem with Budget Constraints Based on Carbon Emission in Neutrosophic Environment
This paper is to integrate among solid transportation
problem, budget constraints and carbon emission with
probable maximum profit. The limits of air pollution and
climate variation are solely dependent by exerting CO2 gas
and rest greenhouse gases due to myriad transportation system.
Henceforth, it is our apt mission to minimize carbon
emission for pollution free environment. Again transportation
system with single objective is hardly applicable to the
situation with more than one criterion. Therefore multi- objective
decision making is incorporated for designing reallife
transportation problem. Due to time pressure, data limitation,
lack of information or measurement errors in practical
problems, there exist some hesitations or suspicions.
Based on the fact, decision maker considers indeterminacy
in the designed problems. To overcome the restriction on
occurrence and non-occurrence of fuzzy and intuitionistic
fuzzy, neutrosophic set is very important and suitable to accommodate
such general structure of problems. Therefore
neutrosophic environment with neutrosophic linear programming,
fuzzy programming and global criterion method are
profiled to search the compromise solution of the multi- objective
transportation problem (MOTP). Thereafter, the performance
of the considered model is useful by evaluating
a numerical example; and then the derived results are compared.
Finally sensitivity analysis and conclusions with upcoming
works of this research are stated hereafter.PID2020-112754GB-I0
B-TIC-640-UGR2
Multi-objective fully intuitionistic fuzzy fixed-charge solid transportation problem
During past few decades, fuzzy decision is an important attention in the areas of science, engineering, economic system,
business, etc. To solve day-to-day problem, researchers use fuzzy data in transportation problem for presenting the uncontrollable
factors; and most of multi-objective transportation problems are solved using goal programming. However, when the
problem contains interval-valued data, then the obtained solution was provided by goal programming may not satisfy by all
decision-makers. In such condition, we consider a fixed-charge solid transportation problem in multi-objective environment
where all the data are intuitionistic fuzzy numbers with membership and non-membership function. The intuitionistic fuzzy
transportation problem transforms into interval-valued problem using (α, β)-cut, and thereafter, it reduces into a deterministic
problem using accuracy function. Also the optimum value of alternative corresponds to the optimum value of accuracy
function. A numerical example is included to illustrate the usefulness of our proposed model. Finally, conclusions and future
works with the study are described.Portuguese Foundation for Science and Technology ("FCT-Fundacao para a Ciencia e a Tecnologia"), through the CIDMA-Center for Research and Development in Mathematics and Applications
UID/MAT/ 04106/2019Spanish Ministry of Economy and Competitiveness, FEDER funds from the European Union
TIN2014-55024-P
TIN2017-86647-
Extending the solid step fixed-charge transportation problem to consider two-stage networks and multi-item shipments
This paper develops a new mathematical model for a capacitated solid step fixed-charge transportation problem. The problem is formulated as a two-stage transportation network and considers the option of shipping multiple items from the plants to the distribution centers (DC) and afterwards from DCs to customers. In order to tackle such an NP-hard problem, we propose two meta-heuristic algorithms; namely, Simulated Annealing (SA) and Imperialist Competitive Algorithm (ICA). Contrary to the previous studies, new neighborhood strategies maintaining the feasibility of the problem are developed. Additionally, the Taguchi method is used to tune the parameters of the algorithms. In order to validate and evaluate the performances of the model and algorithms, the results of the proposed SA and ICA are compared. The computational results show that the proposed algorithms provide relatively good solutions in a reasonable amount of time. Furthermore, the related comparison reveals that the ICA generates superior solutions compared to the ones obtained by the SA algorithm
Managed information gathering and fusion for transient transport problems
This paper deals with vehicular traffic management by communication technologies from Traffic Control Center point of view in road networks. The global goal is to manage the urban traffic by road traffic operations, controlling and interventional possibilities in order to minimize the traffic delays and stops and to improve traffic safety on the roads. This paper focuses on transient transport, when the controlling management is crucial. The aim was to detect the beginning time of the transient traffic on the roads, to gather the most appropriate data and to get reliable information for interventional suggestions. More reliable information can be created by information fusion, several fusion techniques are expounded in this paper. A half-automatic solution with Decision Support System has been developed to help with engineers in suggestions of interventions based on real time traffic data. The information fusion has benefits for Decision Support System: the complementary sensors may fill the gaps of one another, the system is able to detect the changing of the percentage of different vehicle types in traffic. An example of detection and interventional suggestion about transient traffic on transport networks of a little town is presented at the end of the paper. The novelty of this paper is the gathering of information - triggered by the state changing from stationer to transient - from ad hoc channels and combining them with information from developed regular channels. --information gathering,information fusion,Kalman filter,transient traffic,Decision Support System
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