This paper explores the use of the optimization procedures in SAS/OR software with application to the contemporary logistics distribution network design using an integrated multiple criteria decision making approach. Unlike the traditional optimization techniques, the proposed approach, combining analytic hierarchy process (AHP) and goal programming (GP), considers both quantitative and qualita...

The core of artificial intelligence and machine learning is to get computers to solve problems automatically. One of the great tools that attempt to achieve that goal is Genetic Programming (GP). GP is a generalization procedure of the well-known meta-heuristic of Genetic Algorithms (GAs). Meta-heuristics have shown successful performance in solving many combinatorial search problems. In this p...

We extend our analysis of repetitive patterns found in genetic programming genomes to tree based GP. As in linear GP, repetitive patterns are present in large numbers. Size fair crossover limits bloat in automatic programming, preventing the evolution of recurring motifs. We examine these complex properties in detail: e.g. using depth v. size Catalan binary tree shape plots, subgraph and subtre...

In this paper, we address a problem in which a storage space constrained buyer procures a single product in multiple periods from multiple suppliers. The production capacity constrained suppliers offer all-unit quantity discounts. The late deliveries and rejections are also incorporated in sourcing. In addition, we consider transportation cost explicitly in decision making which may vary becaus...

In this paper, we propose new computational intelligence sequential hybrid architectures involving Genetic Programming (GP) and Group Method of Data Handling (GMDH) viz. GP-GMDH, GMDH-GP and recurrent architecture for Genetic Programming (GP) for software cost estimation. Three linear ensembles based on (i) arithmetic mean (ii) geometric mean and (iii) harmonic mean are also developed. We also ...

The purpose of this paper is to present how the fuzzy goal programming (FGP) in the area of mathematical programming (MP) can be efficiently used for modeling and solving agricultural planning problems to achieve the target levels of production of various crops cultivated in different seasons in a year and make the profit by allocating the cultivable land properly and utilising the available pr...

Evolutionary Algorithms (EAs) are routinely applied to solve a large set of optimization problems. Traditionally, their performance in solving those problems is analyzed using the fitness quality and computing time, effect evolutionary operators on both metrics used compare different versions EAs. Nevertheless, scientists face nowadays challenge considering energy efficiency addition computatio...

In this paper, optimal control for stochastic linear singular Takagi–Sugeno (T–S) fuzzy delay system with quadratic performance is obtained using genetic programming (GP). To obtain the optimal control, the solution of matrix Riccati differential equation (MRDE) is computed by solving differential algebraic equation (DAE) using a novel and nontraditional GP approach. The GP solution is equivale...

ABSTRACT: Feasible solutions of Bilevel programming (BLP) problem have to satisfy the optimality conditions of a lower level optimization problem which is defined as part of its constraints. Multiobjective BLP (MOBLP) problems are the special case of BLP problems with multiple objectives at the upper level which require every feasible solution to satisfy the Pareto optimality conditions of a lo...