Mathematical programming model for heat exchanger design through optimization of partial objectives

Mathematical programming can be used for the optimal design of shell-and-tube heat exchangers (STHEs). This paper proposes a mixed integer non-linear programming (MINLP) model for the design of STHEs, following rigorously the standards of the Tubular Exchanger Manufacturers Association (TEMA). Bell–Delaware Method is used for the shell-side calculations. This approach produces a large and non-convex model that cannot be solved to global optimality with the current state of the art solvers. Notwithstanding, it is proposed to perform a sequential optimization approach of partial objective targets through the division of the problem into sets of related equations that are easier to solve. For each one of these problems a heuristic objective function is selected based on the physical behavior of the problem. The global optimal solution of the original problem cannot be ensured even in the case in which each of the sub-problems is solved to global optimality, but at least a very good solution is always guaranteed. Three cases extracted from the literature were studied. The results showed that in all cases the values obtained using the proposed MINLP model containing multiple objective functions improved the values presented in the literature.

A Code for zero-one integer programming, ILLIP-2 : a programming manual for ILLIP-2 /

"UILU-ENG 77 1711."

Optimum network design using NOR and NOR-AND gates by integer programming,

Bibliography: p. 44.

An implicit enumeration program for zero-one integer programming -- ILLIP-2 /

Thesis (M.S.)--Illinois.

A study of the effect of additional inequalities in integer programming for logical design.

Originally presented as the author's thesis (M.S.), University of Illinois at Urbana-Champaign.

Synthesis of optimal networks with NOR and NAND gates by integer programming /

"January 18, 1971."

On the synthesis by integer programming of optimal NOR gate networks for four variable switching functions /

"Supported in part by the National Science Foundation under grant no. NSF GJ-503."

An Implicit enumeration program for zero-one integer programming,

Bibliography: p. 41-42.

Synthesis of optimal double-rail logic networks using NOR-OR gates by integer programming.

"Supported in part by ... Grant no. NSF GJ-503."

Computational experience in all-integer, binary variable, integer programming problems using Gomory's all-integer algorithm,

Bibliographical footnotes.

Implicit enumeration algorithm of integer programming on Illiac IV,

Bibliography: p. 29.

Optimum network design using NOR-OR gates by integer programming.

"Supported in part by ... Grant no. NSF GJ-503."

Heuristic algorithm for computing reversal distance with multigene families via binary integer programming

Hannenhalli and Pevzner developed the first polynomial-time algorithm for the combinatorial problem of sorting of signed genomic data. Their algorithm solves the minimum number of reversals required for rearranging a genome to another when gene duplication is nonexisting. In this paper, we show how to extend the Hannenhalli-Pevzner approach to genomes with multigene families. We propose a new heuristic algorithm to compute the reversal distance between two genomes with multigene families via the concept of binary integer programming without removing gene duplicates. The experimental results on simulated and real biological data demonstrate that the proposed algorithm is able to find the reversal distance accurately. ©2005 IEEE

An Interactive Method of Linear Mixed Integer Multicriteria Optimization

The paper describes a learning-oriented interactive method for solving linear mixed integer problems of multicriteria optimization. The method increases the possibilities of the decision maker (DM) to describe his/her local preferences and at the same time it overcomes some computational difficulties, especially in problems of large dimension. The method is realized in an experimental decision support system for finding the solution of linear mixed integer multicriteria optimization problems.