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Multiple Criteria Optimization: Theory, Computation, and Application
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Mathematical Background Topics from Linear Algebra Single Objective Linear Programming Determining all Alternative Optima Comments about Objective Row Parametric Programming Utility Functions, Nondominated Criterion Vectors and Efficient Points Point Estimate Weighted-sums Approach.Abstract:
Mathematical Background Topics from Linear Algebra Single Objective Linear Programming Determining all Alternative Optima Comments about Objective Row Parametric Programming Utility Functions, Nondominated Criterion Vectors and Efficient Points Point Estimate Weighted-sums Approach Optimal Weighting Vectors, Scaling and Reduced Feasible Region Methods Vector-Maximum Algorithms Goal Programming Filtering and Set Discretization Multiple Objective Linear Fractional Programming Interactive Procedures Interactive Weighted Tchebycheff Procedure Tchebycheff/Weighted-Sums Implementation Applications Future Directions Index.read more
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Portfolio construction on the Athens Stock Exchange: a multiobjective optimization approach
TL;DR: In this article, a single-period multiobjective mixed-integer programming model for equity portfolio construction is proposed to generate the Pareto optimal portfolios, using a variant of the well-known e-constraint method.
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Local approximation of the efficient frontier in robust design
TL;DR: The method eliminates the need of solving the bi-objective problem repeatedly using new preference structures, which is often computationally expensive, and is also applicable to any bi- objective optimization problem.
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A mixed integer goal programming model for discrete values of design requirements in QFD
Elif Kılıç Delice,Zülal Güngör +1 more
TL;DR: In this paper, a mixed integer linear programming (MILP) model considering discrete data is suggested to determine target values for the design requirements (DRs) of a product, with a view to achieving a higher level of overall customer satisfaction.
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Heuristic and exact algorithms for the max-min optimization of the multi-scenario knapsack problem
TL;DR: A kind of surrogate relaxation is introduced to derive upper and lower bounds quickly by solving a continuous knapsack problem, and it is shown that the developed method solves larger instances to optimality faster than the previously published algorithms.
Journal ArticleDOI
Haulage sharing approach to achieve sustainability in material purchasing: New method and numerical applications
TL;DR: In this paper, the authors developed and discussed a new haulage-sharing lot sizing model in which two partners are cooperating in sharing transportation paths and handling units, and a three step methodology based on multi-objective optimization approach is proposed to permit the complete evaluation of the costs and savings that arise with an horizontal cooperation.