The classic approach in robust optimization is to optimize the solution with respect to the worst case scenario. This pessimistic approach yields solutions that perform best if the worst scenario happens, but also usually perform bad on average. A solution that optimizes the average performance on the other hand lacks in worst-case performance guarantee. In practice it is important to find a go...

This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang’s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying t...

Humanitarian relief logistics is one of the most important elements of a relief operation in disaster management. The present work develops a multi-objective robust stochastic programming approach for disaster relief logistics under uncertainty. In our approach, not only demands but also supplies and the cost of procurement and transportation are considered as the uncertain parameters. Furtherm...

In this paper a mixed-integer linear programming (MILP) model is studied for the bi-objective public R&D projects portfolio problem. The proposed approach provides an acceptable compromise between the impact and the number of supported projects. Lagrangian relaxation techniques are considered to get easy computable bounds for the objectives. The experiments show that a solution can be obtained ...

This paper suggests a wavelet transform based multiresolution approach as a viable solution to the problems of storage, retrieval and browsing in a large image database. We also investigate the performance of an optimal uniform mean square quantizer in representing all transform coeecients to ensure that the disk space necessary for storing a multiresolution representation does not exceed that ...

The utopia point of a multicriteria optimization problem is the vector that specifies for each criterion the most favorable feasible value. The Euclidean compromise solution in multicriteria optimization is a solution concept that assigns to a feasible set the alternative with minimal Euclidean distance to the utopia point. This paper provides several axiomatic characterizations of the Euclidea...

The main bottleneck in using optimization in industry is the way uncertainty is handled, which forms the subject of this series of two papers. The first part dealt with the characterization of the nominal solution and proposed an approach to separate the constraint-seeking and the compromise-seeking components of the inputs. This second part reviews various strategies for optimization under unc...

In this paper, the Contiguous Partition Method (CPM) is applied to the optimization of the directivity of difference patterns in monopulse planar array antennas. Since the excitations providing maximum directivity of planar arrays can be analytically computed and because of the excitation matching nature of the CPM, the problem at hand is recast as the synthesis of the difference compromise sol...

The belief that the project manager, a person in charge of the project management (PM), plays a very important role to handle conflicting goals with the usage of all resources through the organization is without doubt. The main purpose of the project management is to minimize total project and crashing cost with the reference to both direct and indirect cost and other related constraints simult...