Agriculture Technology as a Tool to Influence Youth Farming in Ghana

The extent of engagement of the youth going into farming is steadily seen as the modern-day panacea for sustainability and extenuation of food insecurity. Yet, this plodding-shift of the youth has opened new doors for a different problem that needs efficient agricultural resolution. The study examines the correlation between youth farming and the various factors that influence the youth to go into agriculture using data obtained from the Ghanaian youth. We applied Explanatory Factor Analysis (EFA) of the paradigms, with principal component factoring. The results justified using Confirmatory Factor Analysis (CFA) in AMOS and R. The results showed that technology outperforms factors such as motivation, economics, and government policies to significantly influence the youth towards farming. Attitude and knowledge were also found to have an indirect influence on youth farming. The paper contributes to the theoretical influence of technology on the youth and on the practicality of agricultural farming.

Combinatorial auction algorithm for project portfolio selection and scheduling to maximize the net present value

Scheduling projects at the activity level increases the complexity of decision making of project portfolio selection but also expands the search space to include better project portfolios. An integer programming model is formulated for the project portfolio selection and scheduling problem. An iterative multi-unit combinatorial auction algorithm is proposed to select and schedule project portfolios through a distributed bidding mechanism. Two price update schemes are designed to adopt either a standard or an adaptive Walrasian tatonnement process. Computational tests show that the proposed auction algorithm with the adaptive price update scheme selects and schedules project portfolios effectively and maximizes the total net present value. The price profile generated by the algorithm also provides managerial insights for project managers and helps to manage the scarce resources efficiently.

SCHEDULING ALGORITHM BASED ON FOLLOW-UP SHARING CHARACTER FOR POST-EVENT RESPONSE RESOURCE DISTRIBUTION IN LARGE-SCAL DISASTERS

Post-event response planners must develop effective and efficient plans for the proper allocation and distribution of resources to impacted areas （IAs） within a critical time window. To determine the effectiveness and efficiency of distribution plans, this study addresses resource allocation effectiveness losses （RAEL, or losses caused by the mismatch between supply and demand in IAs） and emergency logistics time costs （ELTC, or transportation time of logistics processes under emergency conditions）. Moreover, this study examines a follow-up sharing character （FSC） that coordinates resources among different phases. This research proposes an integrated model （IM） based on this character. This model aims to minimize RAEL and ELTC. Furthermore, the IM combines the time dimension model （TDM）, which coordinates the demands and supplies of all phases in the planning horizon, and the space dimension model （SDM）, which generates a specific distribution plan for the first phase. An analytical solution is obtained for the TDM as per the definition of FSC, after which the SDM is solved through a single-objective linear programming model. After solving the IM effectively, we fred that the proposed methodology fits the emergency circumstance well. Insights derived from the model are also presented in the conclusion.）