Sentence examples for developing a solution approach from inspiring English sources

Shi et al. (2010) developed a mathematical model for optimizing regeneracy system profit by developing a solution approach based on Lagrangian and Gradient algorithm.

To solve these stochastic multi-objective NDP models, we develop a solution approach that explicitly optimizes all objectives under demand uncertainty by simultaneously generating a family of optimal solutions known as the Pareto optimal solution set.

With linear corn demand functions, we develop a solution approach that transforms the original discrete mathematical program with equilibrium constraints (DC-MPEC) into to a solvable mixed integer quadratic programming (MIQP) problem based on Karush Kuhn Tucker (KKT) conditions.

By considering multiple objectives and unknown parameters, the above CLL network was studied by developing a hybrid solution approach based on the IFGP model and three robust counterpart optimization formulations proposed by Soyster, Bertsimas, and Lin.

This paper considers monopolistic, duopolistic and oligopolistic competitions and develops models and a solution approach for CSCND in the markets by the price-dependent demand and deterministic customer utility function.

This study builds on previous work in order to develop a solutions based approach for PNs and their employing general practices wishing to incorporate cervical screening and well women's health care services into their work.

Developing a GA algorithm as a solution approach to the proposed model.  .

The exceptional and void elements, and; The total cost consisted of the fixed setup costs, the variable machine operation costs and the worker salary costs; Developing a GA algorithm as a solution approach to the proposed model.

Because the actions of decision makers may have an impact on the evolution of underlying sources of uncertainty, this endogenous relationship is modeled and a solution approach developed that converges to an equilibrium system state and improves the performance of agents and the system.

By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations.

We developed a customized solution approach based on Lagrangian relaxation that can solve these models efficiently and accurately.