open-pit production scheduling (opps) problem focuses on determining a block sequencing and scheduling to maximize net present value (npv) of the venture under constraints. the scheduling model is critically sensitive to the economic value volatility of block, block weight, and operational capacity. in order to deal with the opps uncertainties, various approaches can be recommended. robust opti...

BACKGROUND To date, patients with glioblastoma still have a bad median overall survival rate despite radiation dose-escalation and combined modality treatment. Neurocognitive decline is a crucial adverse event which may be linked to high doses to the cortex. In a planning study, we investigated the impact of dose constraints to the cerebral cortex and its relation to the organs at risk for glio...

In this paper we discuss the application of a metaheuristic approach based on the Scatter Search to deal with robust optimization of the planning problem in the deploying of the Dense Wavelength Division Multiplexing (DWDM) technology on an existing optical fiber network taking into account, in addition to the forecasted demands, the uncertainty in the survivability requirements. Keyword: Netwo...

Stochastic network design is a general framework for optimizing network connectivity. It has several applications in computational sustainability including spatial conservation planning, pre-disaster network preparation, and river network optimization. A common assumption in previous work has been made that network parameters (e.g., probability of species colonization) are precisely known, whic...

In this study, a two-stage fuzzy robust integer programming (TFRIP) method has been developed for planning environmental management systems under uncertainty. This approach integrates techniques of robust programming and two-stage stochastic programming within a mixed integer linear programming framework. It can facilitate dynamic analysis of capacity-expansion planning for waste management fac...

We describe an efficient method for planning in environments for which prior maps are plagued with uncertainty. Our approach processes the map to determine key areas whose uncertainty is crucial to the planning task. It then incorporates the uncertainty associated with these areas using the recently developed PAO* algorithm to produce a fast, robust solution to the original planning task.

In this paper, a robust optimization approach is proposed to design a dynamic cellular manufacturing system (DCMS) under uncertainty of processing time of products. In addition, a mathematical model considering cell formation, inter-cell design and production planning under a dynamic environment (i.e., product mix and demand are changed in each period) is presented. Therefore, reconfiguration b...