Many studies are performed by researchers about Shell and Tube Heat Exchanger but the Multi-Objective Big Bang-Big Crunch algorithm (MOBBA) technique has never been used in such studies. This paper presents application of Thermal-Economic Multi-Objective Optimization of Shell and Tube Heat Exchanger Using MOBBA. For optimal design of a shell and tube heat exchanger, it was first thermally model...

Reliable location routing problem considers a location problem and a vehicle routing problem in order to select the optimal location of facilities and at the same time the optimal routes for vehicles considering the unexpected failure for facilities in which, all facilities may fail with a probability. In this paper, a bi-objective mathematical model has been developed to minimize the total cos...

This paper proposes a compromise model, based on a new method, to solve the multi-objective large-scale linear programming (MOLSLP) problems with block angular structure involving fuzzy parameters. The problem involves fuzzy parameters in the objective functions and constraints. In this compromise programming method, two concepts are considered simultaneously. First of them is that the optimal ...

delivering perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years due to the global market becoming more competitive. in this paper a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several produ...

data envelopment analysis (dea) is a method to evaluate the relative efficiency of decision making units (dmus). in this method, the issue has always been to determine a set of weights for each dmu which often caused many problems. since the dea models also have the multi-objective linear programming (molp) problems nature, a rational relationship can be established between molp and dea problem...

A control system design problem involves making trade-offs among multiple competing objectives. This paper studies two multiple objective control problems via nonsmooth analysis. First, a new minimax solution approach to the multiple objective linear-quadratic optimal control problem is presented. The solution to this problem is characterized by a set of coupled Riccati equations. Second, the s...

This paper uses integrated Data Envelopment Analysis (DEA) models to rank all extreme and non-extreme efficient Decision Making Units (DMUs) and then applies integrated DEA ranking method as a criterion to modify Genetic Algorithm (GA) for finding Pareto optimal solutions of a Multi Objective Programming (MOP) problem. The researchers have used ranking method as a shortcut way to modify GA to d...

this article addresses a multi-stage flowshop scheduling problem with equal number of unrelated parallel machines. the objective is to minimize the makespan for a given set of jobs in the system. this problem class is np-hard in the strong sense, so a hybrid heuristic method for sequencing and then allocating operations of jobs to machines is developed. a number of test problems are randomly ge...

In the present work, we consider a class of nonlinear optimal control problems, which can be called “optimal control problems in mechanics.” We deal with control systems whose dynamics can be described by a system of Euler-Lagrange or Hamilton equations. Using the variational structure of the solution of the corresponding boundary-value problems, we reduce the initial optimal control problem to...