9,791 research outputs found

    Fixed-Charge Solid Transportation Problem with Budget Constraints Based on Carbon Emission in Neutrosophic Environment

    Get PDF
    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

    Fuzzy bi-objective optimization model for multi-echelon distribution network

    Get PDF
    It is important for modern businesses to search the ways for continuous improvement in performance of their supply chains. The effective coordination and integrated decision making across the supply chain enhances the performance among its various partners in a multi stage network. The partners considered in this paper are product suppliers, processing points (PP), distribution centres (DC) and retail outlets (RO). The network addresses an uncertain environment threatenedby different sources in order to captivate the real world conditions. The uncertain demand of deteriorating products and its dependent costs develop uncertainties in the environment. On the other hand, suppliers and processing points have restricted capacities for the retail outlets’ order amount happened in each period. A bi-objective non-linear fuzzy mathematical model is developed in which the uncertainties are represented by the fuzzy set theory. The proposed model shows cost minimization and best supplier selection coordination under the conditions of capacity constraints, uncertain parameters and product’s deteriorating nature. The fish and fish products give good examples for the proposed model. To solve, the model is converted into crisp form and solved with the help of fuzzy goal programming

    A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain

    Full text link
    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

    Get PDF
    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-

    AI and OR in management of operations: history and trends

    Get PDF
    The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested
    • …
    corecore