The Minimum Cost Flow (MCF) problem is a well-known problem in the area of network optimisation. To tackle this problem, Network Simplex Algorithm (NSA) is the fastest solution method. NSA has three extensions, namely Network Simplex plus Algorithm (NSA+), Dynamic Network Simplex Algorithm (DNSA) and Dynamic Network Simplex plus Algorithm (DNSA+). The objectives of the research reported in this...

multicast routing is one of the most important services in multi radio multi channel (mrmc) wireless mesh networks (wmn). multicast routing performance in wmns could be improved by choosing the best routes and the routes that have minimum interference to reach multicast receivers. in this paper we want to address the multicast routing problem for a given channel assignment in wmns. the channels...

resource limitation in zero time may cause to some profitable projects not to be selected in project selection problem, thus simultaneous project portfolio selection and scheduling problem has received significant attention. in this study, budget, investment costs and earnings are considered to be stochastic. the objectives are maximizing net present values of selected projects and minimizing v...

in this paper, a multi-product single machine scheduling problem with the possibility of producing defected jobs, is considered. we concern rework in the scheduling environment and propose a mixed-integer programming (mip) model for the problem.  based on the philosophy of just-in-time production, minimization of the sum of earliness and tardiness costs is taken into account as the objective fu...

This paper presents a successive approximation method (SAM) for solving a large class of optimal control problems. The proposed analytical-approximate method, successively solves the Two-Point Boundary Value Problem (TPBVP), obtained from the Pontryagin's Maximum Principle (PMP). The convergence of this method is proved and a control design algorithm with low computational complexity is present...

knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering  in which there is no need to  be peculiar about how to select initial values. due to properly converting the task of optimization to an equivalent...