השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| תכנות מטרות רב-מטרתי× | אופטימיזציה רב-מטרתית× | |
|---|---|---|
| תחום | סימולציה | סימולציה |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 1961 | 1896 (concept); 1989–2002 (evolutionary algorithms era) |
| הוגה השיטה≠ | Charnes, A. and Cooper, W. W. | Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al. |
| סוג≠ | Mathematical programming / multi-criteria optimization | Optimization framework |
| מקור מכונן≠ | Charnes, A., Cooper, W. W. (1961). Management Models and Industrial Applications of Linear Programming. Wiley, New York. ISBN: 978-0471148258 | Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester. ISBN: 9780471873396 |
| כינויים | MOGP, Multi-goal programming, Vector goal programming, Multi-criteria goal programming | MOO, Multi-Criteria Optimization, Vector Optimization, Pareto Optimization |
| קשורות≠ | 4 | 3 |
| תקציר≠ | Multi-Objective Goal Programming (MOGP) is a mathematical programming technique that simultaneously pursues several aspirational targets by minimizing weighted deviations from each goal. Rooted in Charnes and Cooper's original goal programming framework (1961), MOGP extends it to handle multiple competing objectives, making it indispensable in operations research, supply chain design, resource allocation, and policy analysis where decision-makers must satisfy — or come close to — multiple conflicting requirements at once. | Multi-Objective Optimization (MOO) is a mathematical and computational framework for finding solutions that simultaneously optimize two or more conflicting objective functions. Rather than collapsing all goals into a single scalar, MOO produces a set of trade-off solutions — the Pareto front — from which a decision-maker selects according to preference. It is widely used in engineering design, operations research, logistics, economics, and policy analysis. |
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