Space division multiplexing (SDM) and elastic optical networking (EON) have been proposed to increase the transmission capacity and flexibility of optical transport networks. The problem of allocating available resources over the EON network is called routing and spectrum assignment (RSA); it is called routing, modulation level, and spectrum assignment (RMLSA) if modulation adaptivity is enabled. Considering SDM adds more flexibility to the resource allocation problem. In this paper, we formulate the routing, modulation level, space, and spectrum assignment (RMLSSA) as integer linear programming (ILP) in a path-based manner for static traffic. Next, the stepwise greedy algorithm (SGA) and four different sorting policies to initiate the algorithm are proposed as a heuristic method to find a near-optimal solution of the RMLSSA problem. Finally, the paper evaluates the effectiveness of sorting policies and the SGA algorithm with different metrics. The performance results show that the SGA initiated with connection demands sorted based on increasing the number of possible space and spectrum assignment layouts (SAL) can achieve the best near-optimal solution for a small network experiment. Moreover, the ascending SAL number (ASN) policy shows the best performance for realistic networks.

The truck allocation problem is an important section of the transportation system in open-pit mines. Most available models for the truck scheduling problem do not directly address the stochastic nature of truck-shovel systems by using multi-objective optimization techniques. This paper presents a chance-constrained goal programming (CCGP) model based on four important goals to estimate the impacts of the uncertainty on the efficiency of truck-shovel systems. The proposed model has been implemented using 11 schedule scenarios and different confidence levels (CLs) for loader’s production to determine the best allocation of trucks in an open-pit copper mine. The results display that the model can handle the quality and quantity of material required to achieve the objectives of the short-term production schedule of the mine in all CLs, even in the highest risk level. This model has a remarkable ability to meet the required objectives in terms of uncertainty in mining operations.