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...

the aim of this study is to propose a new mixed integer linear programming (milp) model to find the minimum required number of yard cranes, rubber tyred gantry cranes (rtgcs), for completion the total amount of works at the end of planning horizon. in other word, we find the optimal number of yard cranes in a container terminal which completes the total amount of works. the paper supports the p...

We combine mixed integer linear programming (MILP) and constraint programming (CP) to solve planning and scheduling problems. Tasks are allocated to facilities using MILP and scheduled using CP, and the two are linked via logic-based Benders decomposition. Tasks assigned to a facility may run in parallel subject to resource constraints (cumulative scheduling). We solve minimum cost problems, as...

This paper introduces $\Delta$-MILP, a powerful variant of the mixed-integer linear programming (MILP) optimization framework to solve NASA's Deep Space Network (DSN) scheduling problem. work is an extension our original MILP (DOI:10.1109/ACCESS.2021.3064928) and inherits many its constructions strengths, including base formulation for DSN scheduling. To provide more feasible schedules with res...

The aim of this work is to propose a mathematical programming model for the Economic Lot Scheduling Problem (ELSP) with performance decay. The main difficulties related to this model are the nonlinearities and/or nonconvexities associated with the dynamic behavior of the system with time. Firstly, the problem is formulated as a Mixed Integer Non Linear Program (MINLP), which is found to be nonc...

In this paper recently developed mixed-integer programming (MIP) tools to the problem of optimal siting and sizing of distributed generators in a distribution network. Here three methodologies for solving the DGPP via mixed-integer linear programming (MILP) and mixed-integer nonlinear programming (MINLP) approaches are compared. The single MILP approach uses the well-known DC linear approximati...

We consider the application of mixed-integer linear programming (MILP) solvers to the minimization of submodular functions. We evaluate common large-scale linear-programming (LP) techniques (e.g., column generation, row generation, dual stabilization) for solving a LP reformulation of the submodular minimization (SM) problem. We present heuristics based on the LP framework and a MILP solver. We...

We first introduce a novel modeling framework, called linear coupled component automata (LCCA), to facilitate the modeling of discrete-continuous dynamical systems with piecewise constant derivatives. Second, we provide a procedure for transforming models in this framework to mixed-integer linear programming (MILP) constraints. Traditionally, such systems have been modeled directly with MILP co...

This short communication presents a generic mathematical programming formulation for Computer-Aided Molecular Design (CAMD). A given CAMD problem, based on target properties, is formulated as a Mixed Integer Linear/Non-Linear Program (MILP/MINLP). The mathematical programming model presented here, which is formulated as an MILP/MINLP problem, considers first-order and second-order molecular gro...

Mixed logical linear programming MLLP is an extension of mixed integer linear pro gramming MILP It can represents the discrete elements of a problem with logical propo sitions and provides a more natural modeling framework than MILP It can also have computational advantages partly because it eliminates integer variables when they serve no purpose provides alternatives to the traditional continu...