Abstract
Aiming at the problem of multiobjective transportation decision-making, a fuzzy compromise method with an improved S-type membership function is proposed. This method not only considers a single objective and evaluates it marginally but also evaluates the overall objective as a whole. First of all, a multiobjective transportation decision-making model is established. Then, each objective function is mapped to a function on the interval [0,1] through the S-type membership function, thereby transforming the multiobjective transportation linear programming model into a multiobjective transportation fuzzy compromise programming model, and its satisfaction is expressed by the global utility function. Finally, through two examples, the results of the example algorithm are compared with the results in the literature, highlighting the superiority of the method. The experimental results show that in the multiobjective transportation decision-making problem, the fuzzy compromise method of the S-type membership function has better flexibility and effectiveness.
Highlights
Multiobjective Transportation DecisionMaking Problem(iv) cqij indicates the unit penalty cost of the q − th objective function, starting point i transport to the destination j
(2) In the past, most of the multiobjective functions only considered the importance of a single-objective function and did not consider the inherent correlation between the objective functions
Assume that the total supply at the starting point is equal to the total demand at the destination
Summary
(iv) cqij indicates the unit penalty cost of the q − th objective function, starting point i transport to the destination j. According to the above-agreed symbols, the multiobjective transportation decision-making problem can be modeled as follows: mn. Q), the optimal value is obtained which is denoted as Lq. If x∗q is the solution of a single-objective function fq(x), so. According to the weight proportion and Φfq, a multiobjective transportation fuzzy compromise programming model with an improved S-type membership function is established: 1/α. (ii) Step 2: according to the optimal solution (x∗q ) of the single-objective function in Step 1, the pay-off matrix is obtained. E optimal solution x∗ is determined by using MATLAB software or an intelligent optimization algorithm, and x∗ is the optimal compromise solution of the original multiobjective transportation decision-making problem (iv) Step 5: according to the preference of decisionmakers, the weight proportion value ω and the global utility factor α are reasonably determined. e optimal solution x∗ is determined by using MATLAB software or an intelligent optimization algorithm, and x∗ is the optimal compromise solution of the original multiobjective transportation decision-making problem
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
