In this paper, an efficient extension of network simplex algorithm is presented. In static scheduling problem, where there is no change in situation, the challenge is that the large problems can be solved in a short time. In this paper, the Static Scheduling problem of Automated Guided Vehicles in container terminal is solved by Network Simplex Algorithm (NSA) and NSA+, which extended the stand...

The simplex algorithm was the first algorithm proposed for linear programming, and although the algorithm is quite fast in practice, no variant of it is known to be polynomial time. The Ellipsoid algorithm is the first polynomial-time algorithm discovered for linear programming. The Ellipsoid algorithm was proposed by the Russian mathematician Shor in 1977 for general convex optimization proble...

The simplex algorithm was the first algorithm proposed for linear programming, and although the algorithm is quite fast in practice, no variant of it is known to be polynomial time. The Ellipsoid algorithm is the first polynomial-time algorithm discovered for linear programming. The Ellipsoid algorithm was proposed by the Russian mathematician Shor in 1977 for general convex optimization proble...

The simplex algorithm was the first algorithm proposed for linear programming, and although the algorithm is quite fast in practice, no variant of it is known to be polynomial time. The Ellipsoid algorithm is the first polynomial-time algorithm discovered for linear programming. The Ellipsoid algorithm was proposed by the Russian mathematician Shor in 1977 for general convex optimization proble...

(a) (b) (c) (d) Figure 1. Illustration of the Algorithm Recall that the correctness of the algorithm depends on the following Lemma: Lemma 1.1. The point d j found by the algorithm must be δ = O(/γ 2) close to some vertex v i. In particular , the corresponding a j O(/γ 2)-covers v i. In order to prove this Lemma, we first show that even if previously found vertices are only δ close to some vert...

In the present paper we investigate Freudenthal's simplex reenement algorithm which can be considered to be the canonical generalization of Bank's well known red reene-ment strategy for triangles. Freudenthal's algorithm subdivides any given (n)-simplex into 2 n subsimplices, in such a way that recursive application results in a stable hierarchy of consistent triangulations. Our investigations ...

Combining meta-heuristics with local search methods is one approach that recently has drawn much attention to design more efficient methods for solving continuous global optimization problems. In this paper, a new algorithm called Simplex Coding Genetic Algorithm (SCGA) is proposed by hybridizing genetic algorithm and simplexbased local search method called Nelder-Mead method. In the SCGA, each...

In most practical problems of linear programming problems with fuzzy cost coefficients, some or all variables are restricted to lie within lower and upper bounds. In this paper, the authors propose a new method for solving such problems called the bounded fuzzy primal simplex algorithm. Some researchers used the linear programming problem with fuzzy cost coefficients as an auxiliary problem for...

Mixed-Initiative Systems (MIS) are hybrid decision systems where collaboration is possible between humans and machines. However, current systems sometimes override user preferences when provided with new ones. We studied linear optimization problems, where the decision maker is specifying preferences for variable values through an iterative process. We proposed a goal programming framework to d...

Recently, a new Dual Network Exterior-Point Simplex Algorithm (DNEPSA) for the Minimum Cost Network Flow Problem (MCNFP) has been developed. In extensive computational studies, DNEPSA performed better than the classical Dual Network Simplex Algorithm (DNSA). In this paper, we present for the first time how to utilize the dynamic trees data structure in the DNEPSA algorithm, in order to achieve ...