In this paper, we introduce a new spatially constrained clustering problem called the max-p-regions problem. It involves the clustering of a set of geographic areas into the maximum number of homogeneous regions such that the value of a spatially extensive regional attribute is above a predefined threshold value. We formulate the max-p-regions problem as a mixed integer programming (MIP) proble...

We consider the planning and scheduling of production in a multitask/multistage batch manufacturing process typical of industries such as chemical manufacturing, food processing, and oil refining. We allow instances in which multiple sequences of tasks may be used to produce end products. We formulate the problem as a mixed-integer linear program and show that the linear programming relaxation ...

We consider the planning and scheduling of production in a multi-task/multi-stage batch manufacturing process typical of industries such as chemical manufacturing, food processing, and oil refining. We allow instances in which multiple sequences of tasks may be used to produce end products. We formulate the problem as a mixed integer linear program and show that the linear programming relaxatio...

We describe a stochastic network interdiction model for deploying radiation detectors at border checkpoints to detect smugglers of nuclear material. The model is stochastic because the smuggler’s origin-destination pair, the type of material, and the level of shielding are known only through a probability distribution when the detectors are installed. We formulate a mixed-integer program for th...

Most of the available literature on optimal well placement has employed numerical simulators in a black box manner linked to an external search engine. In this work, we formulate the contents of that box inside a mixed integer nonlinear programming model for optimal well placement. We provide a unified model that integrates the subsurface, wells, and surface levels of an upstream production pro...

in this paper, we develop a capacitated location-covering model considering interval values for demand and service parameters. we also consider flexibility on distance standard for covering demand nodes by the servers. we use the satisfaction degree to represent the constraint of service capacity. the proposed model belongs to the class of mixed integer programming models. our model can be redu...

Multi-objective optimization is the simultaneous consideration of two or more objective functions that are completely or partially inconflict with each other. The optimality of such optimizations is largely defined through the Pareto optimality. Multiple objective integer linear programs (MOILP) are special cases of multiple criteria decision making problems. Numerous algorithms have been desig...