/pdf/convex-analysisnoer-san-nojin-zhan-nituite-5dl2rbmoyr.pdf

Convex Analysisの二,三の進展について

Vol. 9 Issue 1 pp. 000‐000 There is a growing need for integrating environmentally sound choices into supply-chain management research and practice. Perusal of the literature shows that a broad frame of reference for green supply-chain management (GrSCM) is not adequately developed. Regulatory bodies that formulate regulations to meet societal and ecological concerns to facilitate growth of business and economy also suffer from its absence. A succinct classification to help academicians, researchers and practitioners in understanding integrated GrSCM from a wider perspective is needed. Further, sufficient literature is available to warrant such classification. This paper takes an integrated and fresh look into the area of GrSCM. The literature on GrSCM is covered exhaustively from its conceptualization, primarily taking a ‘reverse logistics angle’. Using the rich body of available literature, including earlier reviews that had relatively limited perspectives, the literature on GrSCM is classified on the basis of the problem context in supply chain’s major influential areas. It is also classified on the basis of methodology and approach adopted. Various mathematical tools/techniques used in literature vis-a-vis the contexts of GrSCM are mapped. A timeline indicating relevant papers is also provided as a ready reference. Finally, the findings and interpretations are summarized, and the main research issues and opportunities are highlighted.

Green supply‐chain management: A state‐of‐the‐art literature review

https://repub.eur.nl/pub/2244/eur_dekker_65.pdf

Quantitative models for reverse logistics: A review

Facility location and supply chain management - A review

Sustainable supply chains: An introduction

A two-level network for recycling sand: A case study

Unmanned Aerial Vehicles (UAVs) can provide significant contributions to information gathering in military missions. UAVs can be used to capture both full motion video and still imagery of specific target locations within the area of interest. In order to improve the effectiveness of a reconnaissance mission, it is important to visit the largest number of interesting target locations possible, taking into consideration operational constraints related to fuel usage between target locations, weather conditions and endurance of the UAV. We model this planning problem as the well-known orienteering problem, which is a generalization of the traveling salesman problem. Given the uncertainty in the military operational environment, robust planning solutions are required. Therefore our model takes into account uncertainty in the fuel usage between targets, for instance due to weather conditions. We report results using different uncertainty sets that specify the degree of uncertainty against which any feasible solution will be protected. We also compare the probability that a solution is feasible for the robust solution on one hand and the solution found with average fuel usage on the other. These probabilities are assessed both by simulation and by derivation of problem specific theoretical bounds on the probability of constraint feasibility. In doing so, we show how the sustainability of a UAV mission can be significantly improved. Additionally, we suggest how the robust solution can be operationalized in a realistic setting, by complementing the robust tour with agility principles

/pdf/robust-uav-mission-planning-9t2778syx8.pdf

Robust UAV mission planning

A new dual problem for convex generalized fractional programs with no duality gap is presented and it is shown how this dual problem can be efficiently solved using a parametric approach. The resulting algorithm can be seen as “dual” to the Dinkelbach-type algorithm for generalized fractional programs since it approximates the optimal objective value of the dual (primal) problem from below. Convergence results for this algorithm are derived and an easy condition to achieve superlinear convergence is also established. Moreover, under some additional assumptions the algorithm also recovers at the same time an optimal solution of the primal problem. We also consider a variant of this new algorithm, based on scaling the “dual” parametric function. The numerical results, in case of quadratic-linear ratios and linear constraints, show that the performance of the new algorithm and its scaled version is superior to that of the Dinkelbach-type algorithms. From the computational results it also appears that contrary to the primal approach, the “dual” approach is less influenced by scaling.

/pdf/a-new-algorithm-for-generalized-fractional-programs-3kf0t4cm5f.pdf

A new algorithm for generalized fractional programs

A two-stage approach to the orienteering problem with stochastic weights

1. Introduction. 2. Discrete Location Models. 3. Location Models and Fractional Programming. 4. Generalized Fractional Programming. 5. Summary and Remarks. Index.

Ana Isabel Barros

Papers

A two-level network for recycling sand: A case study

Robust UAV mission planning

A new algorithm for generalized fractional programs

A two-stage approach to the orienteering problem with stochastic weights

Discrete and Fractional Programming Techniques for Location Models