Reformulation and decomposition of integer programs

In this survey we examine ways to reformulate integer and mixed integer programs. Typically, but not exclusively, one reformulates so as to obtain stronger linear programming relaxations, and hence better bounds for use in a branch-and-bound based algorithm. First we cover in detail reformulations based on decomposition, such as Lagrangean relaxation, Dantzig-Wolfe column generation and the resulting branch-and-price algorithms. This is followed by an examination of Benders’ type algorithms based on projection. Finally we discuss in detail extended formulations involving additional variables that are based on problem structure. These can often be used to provide strengthened a priori formulations. Reformulations obtained by adding cutting planes in the original variables are not treated here.Integer program, Lagrangean relaxation, column generation, branch-and-price, extended formulation, Benders' algorithm

Dynamic Programming to Solve Picking Schedule at the Tea Plantation

The tea picking schedule at PT Perkebunan Ciater isset to be the same for all plantation blocks. Infact, the altitude from sea level and the pruning age of each plantation block is different, this results in thedifference of buds’growth. The implementation of the same pick-ing schedule causesthe quality and quantity of tea buds often couldnot be fulfilled. This research is to determine the precise picking schedule by considering the buds’growth of each plantation block. Two steps are implemented to solve the problem. The first step is to look for picking period and the pattern of buds’quality for each plantation block, which corresponds to the altitude of the location and the pruning age. The regression method is applied in this first step. The buds’quality pattern is then used to determine the cost of de-creasing buds’quality and the costs of the budsthat left in the plantation. The second step is to develop the picking schedule using dy-namic programming, which minimizesthe total cost of picking. In addition to this, we also develop a rolling schedule, which schedule time interval is three days. The modelresults show that the proposed schedule givesa better total cost than the current schedule and the buds’ quality target is easier to achieve. Keywords:Dynamic Programming; Minimizes Cost; Picking Schedul

Smart Microgrids: Overview and Outlook

The idea of changing our energy system from a hierarchical design into a set of nearly independent microgrids becomes feasible with the availability of small renewable energy generators. The smart microgrid concept comes with several challenges in research and engineering targeting load balancing, pricing, consumer integration and home automation. In this paper we first provide an overview on these challenges and present approaches that target the problems identified. While there exist promising algorithms for the particular field, we see a missing integration which specifically targets smart microgrids. Therefore, we propose an architecture that integrates the presented approaches and defines interfaces between the identified components such as generators, storage, smart and \dq{dumb} devices.Comment: presented at the GI Informatik 2012, Braunschweig Germany, Smart Grid Worksho