Applications of mixed integer programming can be found in many industries, such as transportation, healthcare, energy, and finance, their economic impact is significant. It also well known that programs (MIPs) very difficult to solve. Their challenge continues stimulate research the design implementation efficient effective techniques better solve them. In this study, we introduce a novel power...

Nurse scheduling is a topic widely studied due to its overall effect on patient care and hospital performance. This research focuses formulating Mixed Integer Programming (MIP) workforce model as nurse rostering problem. The incorporates multiple objectives of individual preference qualification. approached by categorizing nurses into different hierarchical levels based their qualifications pos...

Mixed-integer conic programming is a generalization of mixed-integer linear programming. In this paper, we present an extension of the duality theory for mixed-integer linear programming (see [4], [11]) to the case of mixed-integer conic programming. In particular, we construct a subadditive dual for mixed-integer conic programming problems. Under a simple condition on the primal problem, we ar...

It has been shown that mixed integer programming methods can e ectively support minimal model, stable model and well-founded model semantics for ground deductive databases. Recently, a novel approach called partial instantiation has been developed which, when integrated with mixed integer programming methods, can handle non-ground logic programs. The goal of this paper is to explore how this in...

dynamic cellular manufacturing systems,   mixed-integer non-linear programming,   production planning, manufacturing attributes   this paper presents a novel mixed-integer non-linear programming model for the design of a dynamic cellular manufacturing system (dcms) based on production planning (pp) decisions and several manufacturing attributes. such an integrated dcms model with an extensive c...

data envelopment analysis (dea) has been widely studied in the literature since its inception with charnes, cooper and rhodes work in 1978. the methodology behind the classical dea method is to determine how much improvements in the outputs (inputs) dimensions is necessary in order to render them efficient. one of the underlying assumptions of this methodology is that the units consume and prod...