Given the diversity of the candidates and complexity of job requirements, and since interviewing is an inherently subjective process, it is an important task to ensure consistent, uniform, efficient and objective interviews that result in high qualit
y recruitment. We propose an interview assistant system to automatically, and in an objective manner, select an optimal set of technical questions (from question banks) personalized for a candidate. This set can help a human interviewer to plan for an upcoming interview of that candidate. We formalize the problem of selecting a set of questions as an integer linear programming problem and use standard solvers to get a solution. We use knowledge graph as background knowledge in this formulation, and derive our objective functions and constraints from it. We use candidate's resume to personalize the selection of questions. We propose an intrinsic evaluation to compare a set of suggested questions with actually asked questions. We also use expert interviewers to comparatively evaluate our approach with a set of reasonable baselines.
The aim of this research was to analyze the current structure of Syrian apple exports,
and highlighting the relative advantage of this crop and its competitive position on
the markets of the key importing countries of Syrian apples. The analysis wa
s based
on secondary data published by FAO during 2000-2013. Descriptive statistical
analyses were used, in addition to estimates of time trend equations to identify the
evolution in quantity, value and price of both Syrian apple exports and imports,
and to determine certain indicators of export competitiveness, besides to applicate
the linear programming model for optimal distribution of Syrian apple exports.
In this research, we present, a linear programming using model.
This model can define the optimal proposal ( with minimum cost
and high efficiency ) in both cases : new net design or exist net
modification.
This research deals with the minimum cost design of reinforced concrete T-beams
according to the Syrian code. The aim is to minimize the total cost of the beam while
respecting all the design requirements. Traditional method depend on a set of supp
ositions,
in the opposite this methodology aim to reach the optimal solution among a set of
constraints with respect the objective function. So that, using this methodology leading to
the minimum cost reinforced section design.
This research is shown that the problem can be formulated in a nonlinear
mathematical programming format.
Several cases are used to explain the applicability of the formulation in accordance
with the current Syrian code. Traditional method of Syrian code has been used to design
sections in this paper, utilizing the nonlinear programming method provided by Lingo14.0
software from LINDO Systems Inc. The comparison of the results shows that important
saving can be obtained at the total cost of a reinforced concrete T-beams design.
Earthmoving is the process of moving and processing soil from one location to another to alter an existing land surface into a desired configuration. Highways, dams, and airports are typical examples of heavy earthmoving projects. Over the years, con
struction managers have devised ways to determine the quantities of material to be moved from one place to another. Various types of soil (soft earth, sand, hard clay, …, etc.) create different level of difficulty of the problem. Earthmoving problem has traditionally been solved using mass diagram method or variety of operational research techniques. However, existing models do not present realistic solution for the problem. Multiple soil types are usually found in cut sections and specific types of soil are required in fill sections. Some soil types in cut sections are not suitable to be used in fill sections and must be disposed of. In this paper a new mathematical programming model is developed to find-out the optimum allocation of earthmoving works. In developing the proposed model, different soil types are considered as well as variation of unit cost with earth quantities moved. Suggested borrow pits and/or disposal sites are introduced to minimize the overall earthmoving cost. The proposed model is entirely formulated using the programming capabilities of VB6 while LINDO is used to solve the formulated model to get the optimum solution. An example project is presented to show how the developed model can be implemented.
The implantation of production processes by using network planning for mass
production is considered essential in machine production and maintenance . This is more
important when producing items as an integrated project that has to be finished in s
pecific
time and with last cost. The network planning is seen from a new perspective because it
studies reaction method and response method to incidental (emergency) events in industrial
production such as ( machine malfunction, shortage in raw materials…) This study uses
probability methods which considers all previous factors when calculating the critical path
in Network plans.
The new approach of this research is using Network planning for programming
production processes in mass production especially in maintenance processes.