11,504 research outputs found
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
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
A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain
We consider a real-world automobile supply chain in which a first-tier supplier serves an assembler and determines its procurement transport planning for a second-tier supplier by using the automobile assembler's demand information, the available capacity of trucks and inventory levels. The proposed fuzzy multi-objective integer linear programming model (FMOILP) improves the transport planning process for material procurement at the first-tier supplier level, which is subject to product groups composed of items that must be ordered together, order lot sizes, fuzzy aspiration levels for inventory and used trucks and uncertain truck maximum available capacities and minimum percentages of demand in stock. Regarding the defuzzification process, we apply two existing methods based on the weighted average method to convert the FMOILP into a crisp MOILP to then apply two different aggregation functions, which we compare, to transform this crisp MOILP into a single objective MILP model. A sensitivity analysis is included to show the impact of the objectives weight vector on the final solutions. The model, based on the full truck load material pick method, provides the quantity of products and number of containers to be loaded per truck and period. An industrial automobile supply chain case study demonstrates the feasibility of applying the proposed model and the solution methodology to a realistic procurement transport planning problem. The results provide lower stock levels and higher occupation of the trucks used to fulfill both demand and minimum inventory requirements than those obtained by the manual spreadsheet-based method. (C) 2014 Elsevier Inc. All rights reserved.This work has been funded partly by the Spanish Ministry of Science and Technology project: Production technology based on the feedback from production, transport and unload planning and the redesign of warehouses decisions in the supply chain (Ref. DPI2010-19977) and by the Universitat Politecnica de Valencia project 'Material Requirement Planning Fourth Generation (MRPIV) (Ref. PAID-05-12)'.Díaz-Madroñero Boluda, FM.; Peidro Payá, D.; Mula, J. (2014). A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain. Applied Mathematical Modelling. 38(23):5705-5725. https://doi.org/10.1016/j.apm.2014.04.053S57055725382
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-
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