A COMPARISON OF PRE-COLLEGE ENRICHMENT PROGRAM PARTICIPANTS AND NON-PARTICIPANTS: COLLEGE ACADEMIC PERFORMANCE MEASURES

This paper analyzes College Grade Point Averages (CGPAs), American College Testing Composite (ACTC) scores and Scholastic Assessment Test Total (SATT) scores of over 1,300 undergraduates at West Virginia University (WVU) who participated in the Health Sciences and Technology Academy (HSTA) to those students who did not (Non-HSTA). Traditionally, pre-college enrichment programs provide academic enrichment to underrepresented youth with the intent of increasing their chances for post-secondary entry and success. Factorial design determined if HSTA participants were better prepared to pursue postsecondary study. Overall, the results reveal that HSTA students outperformed their Non-HSTA counterparts in that there were significant differences in the overall CGPA, ACTC and SATT scores

Tabu Search Heuristics for the Crane Sequencing Problem

Determining the sequence of relocating items (or resources) moved by a crane from existing positions to newly assigned locations during a multiperiod planning horizon is a complex combinatorial optimisation problem, which exists in power plants, shipyards, and warehouses. Therefore, it is essential to develop a good crane route technique to ensure efficient utilisation of the crane as well as to minimize the cost of operating the crane. This problem was defined as the Crane Sequencing Problem (CSP). In this paper, three construction and three improvement algorithms are presented for the CSP. The first improvement heuristic is a simple Tabu Search (TS) heuristic. The second is a probabilistic TS heuristic, and the third adds diversification and intensification strategies to the first. The computational experiments show that the proposed TS heuristics produce high-quality solutions in reasonable computation time

Randomized Routing and Sorting on the Reconfigurable Mesh

In this paper we demonstrate the power of reconfiguration by presenting efficient randomized algorithms for both packet routing and sorting on a reconfigurable mesh connected computer (referred to simply as the mesh from hereon). The run times of these algorithms are better than the best achievable time bounds on a conventional mesh. In particular, we show that permutation routing problem can be solved on a linear array of size n in 3/4n steps, whereas n-1 is the best possible run time without reconfiguration. We also show that permutation routing on an n x n reconfigurable mesh can be done in time n + o(n)using a randomized algorithm or in time 1.25n + o(n) deterministically. In contrast, 2n-2 is the diameter of a conventional mesh and hence routing and sorting will need at least 2n-2 steps on a conventional mesh. In addition we show that the problem of sorting can be solved in time n+ o(n). All these time bounds hold with high probability. The bisection lower bound for both sorting and routing on the mesh is n/2, and hence our algorithms have nearly optimal time bounds

Demonstrating the Efficacy of the Health Sciences and Technology Academy: Using Archival Standardized Test Scores to Analyze an OST College-Preparatory Program for Underserved Youth

To combat educational and health disparities, out-of-school-time (OST) STEM enrichment programs provide services to underserved youth to encourage them to pursue college and health careers. This article describes a study conducted to determine if the Health Sciences and Technology Academy (HSTA) program participants who receive year-round educational interventions to prepare them for STEM and health sciences majors performed better on the West Virginia Educational Standards Test (WESTEST2) than non-participants. This study provides descriptive and inferential statistics, specifically one-way ANOVAs with one-to-one matching based on grade level, gender, race, and GPA at the end of the 8th grade year for 336 students. Statistically significant differences were found favoring HSTA participants on the WESTEST2 math and reading/language scores

A Tabu Search Heuristic for a Generalized Quadratic Assignment Problem

The generalized quadratic assignment problem (GQAP) is the task of assigning a set of facilities to a set of locations such that the sum of the assignment and transportation costs is minimized. The facilities may have different space requirements, and the locations may have varying space capacities. Also, multiple facilities may be assigned to each location such that space capacity is not exceeded. In this paper, an application of the GQAP is presented for assigning a set of machines to a set of locations on the plant floor. Construction algorithms and a simple tabu search heuristic are developed for the GQAP. A set of test problems available in the literature was used to evaluate the performances of the TS heuristic using different construction algorithms. The results show that the simple TS heuristic is effective for solving the GQAP

An Application of an Unequal-Area Facilities Layout Problem with Fixed-Shape Facilities

The unequal-area facility layout problem (UA-FLP) is the problem of locating rectangular facilities on a rectangular floor space such that facilities do not overlap while optimizing some objective. The objective considered in this paper is minimizing the total distance materials travel between facilities. The UA-FLP considered in this paper considers facilities with fixed dimension and was motivated by the investigation of layout options for a production area at the Toyota Motor Manufacturing West Virginia (TMMWV) plant in Buffalo, WV, USA. This paper presents a mathematical model and a genetic algorithm for locating facilities on a continuous plant floor. More specifically, a genetic algorithm, which consists of a boundary search heuristic (BSH), a linear program, and a dual simplex method, is developed for an UA-FLP. To test the performance of the proposed technique, several test problems taken from the literature are used in the analysis. The results show that the proposed heuristic performs well with respect to solution quality and computational time

New Tabu Search Heuristics for the Dynamic Facility Layout Problem

A manufacturing facility is a dynamic system that constantly evolves due to changes such as changes in product demands, product designs, or replacement of production equipment. As a result, the dynamic facility layout problem (DFLP) considers these changes and is defined as the problem of assigning departments to locations during a multi-period planning horizon such that the sum of the material handling and re-arrangement costs is minimised. In this paper, three tabu search (TS) heuristics are presented for this problem. The first heuristic is a simple TS heuristic. The second heuristic adds diversification and intensification strategies to the first, and the third heuristic is a probabilistic TS heuristic. To test the performances of the heuristics, two sets of test problems from the literature are used in the analysis. The results show that the second heuristic out-performs the other proposed heuristics and the heuristics available in the literature

Solution Techniques for a Crane Sequencing Problem

In the areas of power plant maintenance, shipyard and warehouse management, resources (items) assigned to locations need to be relocated. It is essential to develop efficient techniques for relocating items to new locations using a crane such that the sum of the cost of moving the items and the cost of loading/unloading the items is minimised. This problem is defined as the crane sequencing problem (CSP). Since the CSP determines the routes for a crane to relocate items, it is closely related to some variants of the travelling salesman problem. However, the CSP considers the capacities of locations and intermediate drops (i.e. preemptions) during a multiple period planning horizon. In this article, a mathematical model and hybrid ant systems are developed for the CSP. Computational experiments were conducted to evaluate the performances of the proposed techniques, and results show that the proposed heuristics are effective