chance-constrained programming
در نشریات گروه ریاضی-
In this work, multi-objective fractional stochastic solid transportation problem uncertainties are represented using the Weibull distribution. This transformation converts the multi-objective fractional stochastic solid transportation problem into a goal programming problem with chance constraints, incorporating probabilistic constraints into its formulation. Goal programming and hyperbolic membership functions also assist in solving the fractional transportation problem. The proposed models serve as the basis for numerical examples and approaches to solving the problem under validated uncertainty. Furthermore, we conduct a sensitivity analysis to assess the impact of parameter changes on the proposed method.
Keywords: Chance Constrained Programming, Fractional Transportation Problem, Goal Programming, Weibull Distribution -
This paper seeks to address the multi-commodity flow problem in uncertainty conditions, in which the objective function of the problem is of fractional type. The cost coefficients and capacities of the problem are uncertain. The purpose of using uncertainty theory is to deal with unknown factors in the uncertain network. After stating the optimality conditions, the problem is transformed into a certain fractional multi-commodity flow problem by applying the uncertain chance-constrained programming approach. Then, the variable transformation approach is used to transform the nonlinear objective function to its linear form. Finally, two numerical examples are evaluated to verify the efficiency of the proposed formulation.Keywords: Fractional programming, Uncertainty theory, Belief degree, Multi-commodity flow problem, Chance-constrained programming
-
Sustainable Waste Management Using Multiple Criteria Decision Making and Fractional Stochastic Programming
AbstractThis paper manages to develop a chance constrained fractional modeling of the waste management taking systems sustainability indices into consideration. Due to the fact that there are some approaches for dealing with the city waste management, but the use of the one that has big positive impacts on the economic and social dimensions of sustainability and least impacts on the environmental side of the problem might of the most concern. To deal with this issue, related city engineers and managers are asked to present their ideas on this problem by filling a questionnaire. Author takes these view point into consideration and then by using fuzzy TOPSIS as a decision making tool for ranking the strategies proposed to city engineers and then those strategies with the highest ranking and implementable in our city was employed for continuation of this study. Once appropriate strategies with sustainability consideration are determined, a stochastic programming model is proposed and a linearization technique was recommended to solve that. A sample case problem is used for presentation purposes.
Keywords: Management of wastes, Chance constrained programming, Fuzzy TOPSIS -
A fractional minimal cost flow problem under linear type belief degree based uncertainty is studied for the first time. This type of uncertainty is useful when no historical information of an uncertain event is available. The problem is crisped using an uncertain chance-constrained programming approach and its non-linear objective function is linearized by a variable changing approach. An illustrative example is solved to prove the efficiency of the proposed formulation.Keywords: Uncertainty theory, Belief degree, Fractional minimal cost flow problem, Chance-constrained programming
-
In this paper, the capacitated location-routing problem with fuzzy demands (CLRP-FD) is considered. The CLRP-FD is composed of two well-known problems: facility location problem and vehicle routing problem. The problem has many real-life applications of which some have been addressed in the literature such as management of hazardous wastes and food and drink distribution. In CLRP-FD, a set of customers with fuzzy demands should be supplied by a fleet of vehicles that start and end their tours at a single depot. Moreover, the vehicles and the depots have a limited capacity. To model this problem, a fuzzy chance-constrained programming is designed based on fuzzy credibility theory. To solve the CLRP-FD, a hybrid heuristic algorithm (HHA) including two main phases is proposed. In the first phase, an initial population of solutions is generated by the greedy clustering method (GCM) obtained from the literature of the problem, while in the second phase, a genetic algorithm is applied for further improvement of the solutions of first phase. While the first phase of the HHA consists of four steps, the second phase includes two main steps. To achieve the best value of the major parameter of the model, named dispatcher preference index, and to analyze its influence on the changes of the final solution, numerical experiments with different sizes on the number of customers and candidate depots are carried out. The computational results show that the HHA is efficient so that it has improved all solutions that obtained from the GCM. Finally, performance of the proposed model to the similar model exists in the literature is evaluated by several standard test problems of the ýCLRP.ýKeywords: Capacitated location, routing problem, Fuzzy demand, Credibility theory, Stochastic simulation, Fuzzy, chance constrained programming, Genetic ýalgorithm
- نتایج بر اساس تاریخ انتشار مرتب شدهاند.
- کلیدواژه مورد نظر شما تنها در فیلد کلیدواژگان مقالات جستجو شدهاست. به منظور حذف نتایج غیر مرتبط، جستجو تنها در مقالات مجلاتی انجام شده که با مجله ماخذ هم موضوع هستند.
- در صورتی که میخواهید جستجو را در همه موضوعات و با شرایط دیگر تکرار کنید به صفحه جستجوی پیشرفته مجلات مراجعه کنید.