Fig. 1 Multilevel group and network decisions in MSNs and potential conflicts between these decisions at a level and across levels More about this image found in Multilevel group and network decisions in MSNs and potential conflicts betw...

Fig. 2 Depiction of nodes and edges connecting nodes in an MSN and node and edge disruptions and their impact on the MSN connectivity More about this image found in Depiction of nodes and edges connecting nodes in an MSN and node and edge d...

Fig. 3 Information flow connecting the network, manufacturer group, supplier group, and customer group decisions across two levels (levels 1 and 2) in a manufacturing supply network More about this image found in Information flow connecting the network, manufacturer group, supplier group...

Fig. 4 The structure of the c-cDSP construct More about this image found in The structure of the c-cDSP construct

Fig. 5 An MSN design configuration with multiple nodes at and across multiple groups and multiple edges connecting the nodes. Situations of node and edge disruptions and their impact on connectivity in the MSN are depicted. More about this image found in An MSN design configuration with multiple nodes at and across multiple grou...

Fig. 6 Framework to support co-design exploration of MSNs for resilience—the CoDE-MR framework More about this image found in Framework to support co-design exploration of MSNs for resilience—the CoDE-...

Fig. 7 Edges connecting the enterprises (nodes) in the manufacturer, supplier, and customer groups across levels 1 and 2 in the steel MSN More about this image found in Edges connecting the enterprises (nodes) in the manufacturer, supplier, and...

Fig. 8 Information flow connecting the network decisions, manufacturer group decisions, and supplier group decisions across levels 1 and 2 in the steel MSN More about this image found in Information flow connecting the network decisions, manufacturer group decis...

Fig. 9 The iSOM plots for goals ( G g ) for the steel MSN problem. The grid points highlighted using red hexagons in the iSOM goals plots represent the initial satisficing solutions regions for goals. More about this image found in The iSOM plots for goals ( G g ) for the steel MSN problem. The grid...

Fig. 10 Satisficing solution plots for goals after relaxation of satisficing limits. The black hexagons represent the common satisficing grid points for the network, manufacturer group, and supplier group goals across levels 1 and 2. More about this image found in Satisficing solution plots for goals after relaxation of satisficing limits...

Fig. 11 The network structure and materials flow in the steel MSN corresponding to design variables for scenario 97 in Tables 6 – 8 . The ovals represent the nodes in each group, and the directed arrows represent the edges connecting the nodes. More about this image found in The network structure and materials flow in the steel MSN corresponding to ...

Fig. 1 The edges e i j in our model have costs c i j that behave as continuous random variables with associated probability distribution functions f i j , making the costs incurred in transitions T i j not known a priori. However, we assume that the f... More about this image found in The edges e i j in our model have costs c i j that ...

Fig. 2 The g-cost g ( n i , x ) in our model is treated as a probability density function. To satisfy the node constraints, given by admissible intervals [ a i , b i ] , the probability that g ( n i , x ) lies within g k I i must be higher or... More about this image found in The g-cost g ( n i , x ) in our model is treated as a probabi...

Fig. 3 Our methodology is divided into two main sections: graph construction and plan optimization. Graph construction is done by creating a configuration graph of a discretized environment, and then time-augmenting it into a state graph. Plan optimization is done through a novel stochastic extens... More about this image found in Our methodology is divided into two main sections: graph construction and p...

Fig. 4 The environment discretization process involves taking each entity, which could be obstacles or agents, sampling control points on their boundaries and connecting them with line segments. The discretized representation (darker gray) is assumed to correspond exactly to the agents geometry fr... More about this image found in The environment discretization process involves taking each entity, which c...

Fig. 5 Sampling is done after all entities in the environment are discretized. Our methodology employs a PRM approach that finds configurations u i that are collision-free with respect to static obstacles only. We show two examples of the sampling process, with different choices of agent ... More about this image found in Sampling is done after all entities in the environment are discretized. Our...

Fig. 6 Each node of the original configuration graph G u is assigned a number k of admissible intervals which restrict the allowed range of costs incurred once that node is reached. In our dynamic motion planning context, the cost is equivalent to time. When transitioning from G... More about this image found in Each node of the original configuration graph G u is assigned a nu...