Model and Combinatorial Optimization Methods for Tactical Planning in Closed-Loop Supply Chains

International audienc

A Metaheuristic for Tactical Inventory Planning in Closed-Loop Supply Chains

International audienc

Tactical Supply Chain Distribution Planning In The Telecommunications Service Industry

Supply chains are ubiquitous across industries and a considerable e ort has been invested in supply chain management techniques over the last two decades. In equipment-intensive service industries, it often involves repair operations. In this context, tactical inventory planning is concerned with optimally planning supplies and repairs based on demand forecasts and in face of con icting business objectives. It is based on a case study in the telecommunications sector where large quantities and varieties of spare parts are required for service maintenance and repair tasks at customer premises or company exchanges. Speci cally, we consider a multi-echelon spare parts supply chain and tackle the problem of determining an optimal stock distribution plan given a demand forecast. We propose a mixed integer programming and a metaheuristic approach to this problem. The model is open to a variety of network topologies, site functions and transfer policies. It also accommodates multiple objectives by the means of a weighted cost function. We report experiments on pseudo-random instances designed to evaluate plan quality and impact of cost weightings. In particular, we show how appropriate weightings allow to emulate common planning strategies (e.g., just-in-time replenishment, minimal repair). We also assess plan quality and system performance against di erent classes of pseudo-random instances featuring different volume and distribution of stock and demand

Strategies for handling uncertainty in tactical distribution planning - an empirical study

International audienc

Effect of a legume cover crop (Mucuna pruriens var. utilis) on soil carbon in an ultisol under maize cultivation in southern Benin

Long term fallow is no longer possible in densely populated tropical areas, but legume cover crops can help maintain soil fertility. Our work aimed to study changes in soil carbon in a sandy loam Ultisol in Benin, which involved a 12-year experiment on three maize cropping systems under manual tillage: traditional no-input cultivation (T), mineral fertilized cultivation (NPK), and association with Mucuna pruriens (M). The origin of soil carbon was also determined through the natural abundance of soil and biomass C-13. In T, NPK and M changes in soil carbon at 0-40 cm were -0.2, +0.2 and +1.3 t C ha(-1) yr(-1), with residue carbon amounting to 3.5, 6.4 and 10.0 t C ha(-1) yr(-1), respectively. After 12 years of experimentation, carbon originating from maize in litter-plus-soil (0-40 cm) represented less than 4% of both total carbon and overall maize residue carbon. In contrast, carbon originating from mucuna in litter-plus-soil represented more than 50% of both total carbon and overall mucuna residue carbon in M, possibly due to accelerated mineralization of native soil carbon (priming effect) and slow mulch decomposition. Carbon originating from weeds in litter-plus-soil represented c. 10% of both total carbon and overall weed residue carbon in T and NPK. Thus mucuna mulch was very effective in promoting carbon sequestration in the soil studied

hp-DGFEM for Partial Differential Equations with Nonnegative Characteristic Form

Presented as Invited Lecture at the International Symposium on Discontinuous Galerkin Methods: Theory, Computation and Applications, in Newport, RI, USA.\ud \ud We develop the error analysis for the hp-version of a discontinuous finite element approximation to second-order partial differential equations with nonnegative characteristic form. This class of equations includes classical examples of second-order elliptic and parabolic equations, first-order hyperbolic equations, as well as equations of mixed type. We establish an a priori error bound for the method which is of optimal order in the mesh size h and 1 order less than optimal in the polynomial degree p. In the particular case of a first-order hyperbolic equation the error bound is optimal in h and 1/2 an order less than optimal in p

A Combinatorial Optimisation Approach For Closed-Loop Supply Chains Inventory Planning With Deterministic Demands

Supply chains in equipment-intensive service industries often involve repair operations. In this context, tactical inventory planning is concerned with optimally planning supplies and repairs based on demand forecasts and in the face of conflicting business objectives. This paper considers closed-loop supply chains and proposes a mixed-integer programming model and a metaheuristic approach to this problem. The model is open to a variety of network topologies, site functions and transfer policies. It also accommodates multiple objectives by the means of a weighted cost function. We report experiments on pseudo-random instances designed to evaluate plan quality and impact of cost weightings. In particular, we show how appropriate weightings allow to implement common planning strategies (e.g., just-in-time replenishment, minimal repair

An investigation of heuristic decomposition to tackle workforce scheduling and routing with time-dependent activities constraints

This paper presents an investigation into the application of heuristic decomposition and mixed-integer programming to tackle workforce scheduling and routing problems (WSRP) that involve timedependent activities constraints. These constraints refer to time-wise dependencies between activities. The decomposition method investigated here is called repeated decomposition with con ict repair (RDCR) and it consists of repeatedly applying a phase of problem decomposition and sub-problem solving, followed by a phase dedicated to con ict repair. In order to deal with the time-dependent activities constraints, the problem decomposition puts all activities associated to the same location and their dependent activities in the same sub-problem. This is to guarantee the satisfaction of time-dependent activities constraints as each sub-problem is solved exactly with an exact solver. Once the assignments are made, the time windows of dependent activities are fixed even if those activities are subject to the repair phase. The paper presents an experimental study to assess the performance of the decomposition method when compared to a tailored greedy heuristic. Results show that the proposed RDCR is an effective approach to harness the power of mixed integer programming solvers to tackle the diffcult and highly constrained WSRP in practical computational time. Also, an analysis is conducted in order to understand how the performance of the different solution methods (the decomposition, the tailored heuristic and the MIP solver) is accected by the size of the problem instances and other features of the problem. The paper concludes by making some recommendations on the type of method that could be more suitable for different problem sizes