GENERATION EXPANSION PLANNING USING BENDERS’ DECOMPOSITION AND GENERALIZED NETWORKS

This paper presents an optimization model and its application to a generation expansion planning problem. The proposed model has a generalized network structure and is exploited effectively by Benders’ decomposition algorithm, where a master problem generates trial expansion plans and a set of subproblems compute production cost and system reliability for the trial plan. The applicability of our decomposition algorithm is demonstrated in the case study of Korea's generation expansion planning. The results demonstrate that the model is a practical and flexible tool in solving realistic long-range generation planning problems

Manpower Modeling and Sensitivity Analysis for Afghan Education Policy

This paper provides a demand based balance of flow manpower model premised in mathematical programming to provide insight into the potential futures of the Afghan Education System. Over the previous three decades, torn from multiple wars and an intolerant governing regime, the education system in Afghanistan has been decimated. Over the past 10 years Afghanistan and the international community have dedicated a substantial amount of resources to educate the youth of Afghanistan. By forecasting student demand we are able to determine points of friction in the teacher production policy regarding grade level, gender, and province across a medium-term time horizon. We modify the model to provide sensitivity analysis to inform policies. Examples of such policies are accounting for the length of teacher training programs and encouragement of inter-provincial teacher moves. By later applying a stochastic optimization model potential outcomes regarding changes in teacher retention attributed to policy decisions, incentives to teach, or security concerns are highlighted. This model was developed in support of the validation of a large scale simulation regarding the same subject

Utilizing the Surrogate Dual Bound in Capacity Planning with Economies of Scale

Minimizing a nondecreasing separable concave cost function over a polyhedral set arises in capacity planning problems where economies of scale and fixed costs are significant, as well as production planning when a learning effect results in decreasing marginal costs. This is an NP-hard combinatorial problem in which the extreme points of the polyhedral set must be enumerated, each of them a local optimum. Branch-and-bound methods have been frequently used to solve these problems. Although it has been shown that in general the bound provided by the surrogate dual is tighter than that of the Lagrangian dual, the latter has generally been preferred because of the apparent computational intractability of the surrogate dual problem. In this paper we describe a branch-and-bound algorithm that exploits the superior surrogate dual bound in a branch-and-bound algorithm without explicitly solving the dual problem. This is accomplished by determining the feasibility of a set of linear inequalities

A Hybrid Benders/genetic algorithm for vehicle routing and scheduling problem

This paper presents an optimization model and its application to a classical vehicle routing problem. The proposed model is exploited effectively by the hybrid Benders/genetic algorithm which is based on the solution framework of Benders’ decomposition algorithm, together with the use of genetic algorithm to effectively reduce the computational difficulty. The applicability of the hybrid algorithm is demonstrated in the case study of the Rockwell Collin’s fleet management plan. The results demonstrate that the model is a practical and flexible tool in solving realistic fleet management planning problems

Shelf-life Assessment on European Cucumber Based on Accelerated Temperature–Humidity Stresses

The supply chain has been significantly impacted recently, and as a result the handling of products at the delivery and supply stage is of great importance. Currently, the agronomic industry is one of the most studied, but the reliability of harvests is not usually evaluated. This study uses a novel reliability analysis with an accelerated life test to expose the European cucumber (Cucumis sativus L.) to accelerated temperature and humidity conditions. The objective is to observe the effect of both factors on the deterioration of the product. The analysis includes a degradation analysis to determine the significant factors causing degradation, followed by an accelerated life test (ALT) to determine the product’s shelf life. Finally, through the development of a reliability model, storage times for cucumbers under normal storage conditions are predicted