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In this paper, we are interested in modelling and solving a flow and resource planning problem related to the trade-in, treatment and resale of pre-owned consumer electronic products. This problem is motivated and inspired by the flows and the processes of the company Recommerce Group, which mainly handles traded-in used smartphones in Europe, but also used tablets, smartwatches, game consoles, laptops, etc. Collected products must be directed to refurbishment centres. After having been recorded, cleaned, tested and reset, they may be refurbished, or remanufactured by a subcontractor. They may also remain in their initial state. Finally, they are sold on diversified channels. This problem can be generalised to other refurbishment and remanufacturing activities of used consumer electronic products. We first formulate the problem as a mixed-integer linear program and show its NP-hardness. In order to solve large size real-life instances, mixed-integer programming based heuristic approaches are proposed. Extensive computational experiments on realistic instances are conducted to show the advantages and the limits of the proposed approaches. Several managerial insights are investigated and analysed. [ABSTRACT FROM AUTHOR]

Many real-life applications are modelled using hierarchical decision-making in which: an upper-level optimisation task is constrained by a lower-level one. Such class of optimisation problems is referred in the literature as Bi-Level Optimisation Problems (BLOPs). Most of the proposed methods tackled the single-objective continuous case adhering to some regularity assumptions. This is at odds with real-world problems which involve mainly discrete variables and expensive objective function evaluations. Besides, the optimisation process becomes exorbitantly time-consuming, especially when optimising several objectives at each level. For this reason, the Multi-objective variant (MBLOP) remains relatively less explored and the number of methods tackling the combinatorial case is much reduced. Motivated by these observations, we propose in this work an elitist decomposition-based evolutionary algorithm to solve MBLOPs, called ECODBEMA. The basic idea of our proposal is to handle, decomposition, elitism and multithreading mechanisms to cope with the MBLOP's high complexity. ECODBEMA is applied to the production–distribution problem and to a sustainable end-of-life products disassembly case-study based on real-data of Aix-en-Provence French city. We compared the optimal solutions of an exact method using CPLEX solver with near-optimal solutions obtained by ECODBEMA. The statistical results show the significant outperformance of ECODBEMA against other multi-objective bi-level optimisation algorithms. [ABSTRACT FROM AUTHOR]

This research aims to solve an integrated production, storage and distribution planning problem in a multi-level multi-product logistics system. The work was conducted in collaboration with a leading mining industry. The present research presents a mixed-integer linear program inspired by the classical Multi-Level Lot-Sizing model to solve the problem. It combines several aspects related to (1) multi-level and multi-product production units, (2) multi-level and multi-product storage units and (3) train transportation with time windows. Besides the standard features of lot-sizing problems, this work encompasses further aspects related to mining activity precisely and, more generally, to the structural specifications of continuous production processes. The objective is to hierarchically satisfy deterministic demand, minimise the total number of switch-offs of production units, and minimise total operational costs. On a sizeable real data-set obtained from our industrial partner, we demonstrate the benefit of integrating decisions in terms of improving demand satisfaction rates, increasing resource efficiency, and minimising total operational costs. In addition, we study the cost structure and provide a detailed cost sensitivity analysis. Finally, this work evaluates the upstream and downstream propagation of decisions in the logistics system and underlines the benefits in terms of flexibility offered by the global approach. [ABSTRACT FROM AUTHOR]