Since the model involves three objective functions, using multi-objective solution methodology is necessary.
A mathematical model is designed for a CLSC that involves three objective functions of maximizing the profit, minimizing the total risk and shortages of products.
The problem formulation involves two objective functions: the minimization of the transportation fare and the maximization of the transported gas volume.
Pishvaee et al. (2010) designed a bi-objective model for a SC which involves two objective functions of maximizing responsiveness and minimizing costs.
Both BioGP and EvoNN were compared for subsequent constrained bi-objective optimization studies for the SMB reactor involving four objectives.
This study develops a new multi-objective simulation optimization model involving four objectives: minimizations of (i) the total sampling costs for monitoring contaminant plume, (ii) mass estimation error, (iii) the first moment estimation error, and (iv) the second moment estimation error of the contaminant plume, for LTGM network design problems.
Minimizing cost while maximizing comfort while buying a car, and maximizing performance whilst minimizing fuel consumption and emission of pollutants of a vehicle are examples of multiobjective optimization problems involving two and three objectives, respectively.
A few sample optimization problems involving two and three objective functions are solved, both for the operation of an existing plant (which is almost trivial), as well as, for the design of new plants (associated with a higher degree of freedom).
China is now navigating a complex economic transition that involves three sometimes-conflicting objectives: creating a market-based consumer economy; reforming the financial system; and ensuring an orderly slowdown that avoids the economic collapse often accompanying industrial restructuring and financial liberalisation.
The proposed method primarily involves three stage multi-objective (travel distance minimization, operational cost minimization, and psychological cost minimization), mixed-integer linear programming models.
The problem is formulated as a multi-objective optimal control problem that involves four conflicting objective functions.
