PMMA composites and solids of complexes of formulas [AgX(P− P)] n [n = 1 and 2; X = Cl, NO 3 , ClO 4 , CF 3 COO, and OTf; P−P = dppb, xantphos, (PR 2 ) 2 C 2 B 10 H 10 (R = Ph and i Pr)] display the whole palette of colors from blue to red upon selection of the anionic ligand (X) and the diphosphane (P−P). The diphosphane seems to play the most important role in tuning the emission energy and thermally activated delayed fluorescence (TADF) behavior. The PMMA composites of the complexes exhibit higher quantum yields than that of the diphosphane ligands and those with dppb are between 28 and 53%. Remarkably, instead of blue-green emissions which dominate the luminescence of silver diphosphane complexes in rigid phases, those with carborane diphosphanes are yellow-orange or orange-red emitters. Theoretical studies have been carried out for complexes with P−P = dppb, X = Cl; P−P = dppic, X = NO 3 ; P−P = dppcc, X = Cl, NO 3 , and OTf and the mononuclear complexes [AgX(xantphos)] (X = Cl, Br). Optimization of the first excited triplet state was only possible for [AgX-(xantphos)] (X = Cl and Br). A mixed MLCT and MC nature could be attributed to the S 0 → T 1 transition in these threecoordinated complexes.

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This paper proposes a matheuristic algorithm based on a column generation structure for the capacitated vehicle routing problem with three-dimensional loading constraints (3L–CVRP). In the column generation approach, the master problem is responsible for managing the selection of best-set routes. In contrast, the slave problem is responsible for solving a shorter restricted route problem (CSP, Constrained Shortest Path) for generating columns (feasible routes). The CSP is not necessarily solved to optimality. In addition, a greedy randomized adaptive search procedure (GRASP) algorithm is used to verify the packing constraints. The master problem begins with a set of feasible routes obtained through a multi-start randomized constructive algorithm (MSRCA) heuristic for the multi-container loading problem (3D–BPP, three-dimensional bin packing problem). The MSRCA consists of finding valid routes considering the customers' best packing (packing first-route second). The efficiency of the proposed approach has been validated by a set of benchmark instances from the literature. The results show the efficiency of the proposed approach and conclude that the slave problem is too complex and computationally expensive to solve through a MIP.