A Mixed Global Optimization Algorithm and Its Application in Packing

Packing problems are categorized as NP-complete．Traditional optimization methods have difficulties to deal with such problems effectively．Recently，genetic algorithms （GA） and simulation annealing algorithms （SAA） were resorted to，but their efficiency to locate a precise result was not quite satisfactory．This paper proposes combining a heuristic random searching strategy with a local optimization algorithm，and names it Mixed Global Optimization Algorithm （MGOA） to overcome the difficulties．Multi-object optimization model is formulated on a simplified satellite cabin packing problem，and taking its known optimal solution as the criteria of evaluation，MGOA is superior to the Multiplier Algorithm and an Improved GA in term of solution quality and efficiency．Therefore，the proposed MGOA has shown some potential to deal with packing problems with good expectation．