# SMU OREM 4390 - Multi-goal Network Optimization (21 pages)

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## Multi-goal Network Optimization

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## Multi-goal Network Optimization

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Pages:
21
School:
Southern Methodist University
Course:
Orem 4390 - Senior Design
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1985 06 Spring 1985 SOUTHERN METHODIST UNIVI OKA Multi goal Network Optimization Buddy Rhoads 4 OKA Multi goal Network Optimization Buddy Rhoads OREM 4390 May 13 1985 S DEPARTMENT OF OPERATIONS RESEARCH AND ENGINEERING MANAGEMENT SCHOOL OF ENGINEERING AND APPLIED SCIENCE DALLAS TEXAS 75275 OKA Multi goal Network Optimization Buddy Rhoads OREM 4390 May 13 1985 OKA is an interactive network optimization program that solves multi goal network problems After given a set of arcs with multiple costs and limits for those arcs OKA solves the network for both goals giving the best and worst possible situations for each goal OKA then allows for weights to be set on each of the goals and will then re evaluate the model and present a graphical analysis of each cost in relation to its best and worst possible cost In order to test OKA a network problem based on school integration was modeled to have multiple goals The first goal was to minimize the distance traveled by students while the second goal was to minimize penalty costs These penalty costs are assessed when a school exceeds or does not meet its minority requirements OKA was initially coded in the C programming language by Dr Richard Barr of the Operations Research Department at Southern Methodist University Dr Barr took existing FORTRAN code using the Out of Kilter algorithm and converted it to C Originally the code only solved single goal network problems and included no user interaction In order to make the program multi goal additional input data needed to be supplied in the input file Each arc now needed to have multiple costs one for each goal These costs are then multiplied by given weights to compute a single weighted cost for each arc in the model The model is then processed by the Out of Kilter algorithm which returns a minimum cost for the model and the foiws for each arc These flows are then used to compute costs for each criterion by multiplying the flows by the original costs from the input data Before this

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