This paper describes the multidisciplinary optimization of an airship with unconventional configuration. The shape of the airship is based upon two semi-ellipsoids, whose axis ratios can be altered for optimization purpose. The parameters to optimize are volume, ratio between longitudinal and lateral semi-axis, ratio between vertical and lateral semi-axis, percentage of the top surface covered by photovoltaic films, and dimension of the tail. The objective of the optimization is to reduce the mass of the airship by keeping the equilibrium between buoyancy and weight as a constraint, reaching the design speed while maintaining the static longitudinal stability of the vehicle. The mathematical model developed to evaluate airship features includes the computation of the ballonet volume, a weight breakdown, considerations about the energy storage for night operations, the power system, and the stability. Six heuristic optimization strategies have been applied to achieve the best solution; some case studies have been developed, and the final optimal configurations found by algorithms have been analyzed to validate the optimization framework. The approach demonstrates that the heuristic optimization strategies used are good tools for the conceptual design of unconventional airship since this problem requires a multidisciplinary approach and several parameters including aerodynamics, propulsion, mass breakdown, aerostatics, and stability. These parameters are strongly dependent on each other and they must be considered together to obtain an optimum and balanced design. Nomenclature a 1 = major longitudinal semi-axis, m a 2 = minor longitudinal semi-axis, m B F = buoyancy, N b = transversal semi-axis, m c = vertical semi-axis, m C D0 = matrix with values of C D0 [5 × 2] C L AoA = matrix with values of C L AoA [5 × 2] C M AoA = matrix with values of C M AoA 5 × 2 CB % = matrix with values of CB% [5 × 2] CB % = center of buoyancy divided by a 1 CB pos = longitudinal distance between ellipsoid center and center of buoyancy, m C D0 = coefficient of drag for 0 angle of attack C D Hull = volumetric drag coefficient of the airship hull C D HT = coefficient of drag of the horizontal tail C D VT = coefficient of drag of the vertical tail C HT sym = chord of the horizontal tail on the symmetry axis, m C HT tip = chord of the horizontal tail at the tip, m C Li = nondimensional coefficient of lift for given angle of attack C L alphaTail = derivative of the tail lift aerodynamic coefficient with angle of attack, 1∕rad C M AoA= coefficient of moment for given angle of attack around center of buoyancy C 1 , C 2 , C 3 = coefficients representing error in constraints satisfaction EnSt Batt = energy stored in lithium-polymer batteries, W · h EnSt RFC = energy stored in regenerative fuel cells, W · h ENtoM Batt = ratio of energy stored to mass of lithiumpolymer batteries, W · h∕kg ENtoM RFC = ratio of energy stored to mass of regenerative fuel cell, W · h∕kg F = fitness function FLMtoTSRF = ratio of solar films to top envelope surface g = ...