Sid-Ali Addouche

Multi-ant colonies algorithms for the VRPSPDTW

The vehicle routing problem with simultaneous pickups and deliveries and time windows (VRP-SPDTW) is the problem of optimally integrating forward (good distribution) and reverse logistics (returning materials) for cost saving and environmental protection. We constructed a general mixed integer programming model of VRP-SPDTW. We present an Improved Ant Colony System (ACS) for the VRPSPDTW (Vehicle Routing Problem with Simultaneous Pick-up and Delivery with Time Windows). We submit adaptations and additions to the different solutions for VRPSPDTW. The real treated problem is to minimize the number of bus fleet that have to serve several schools (stations) for pick-up and delivery of different groups of students at different time windows. In detail, this problem is particularly complex. The significant improvement is to take into account the individual time windows, the time of service in each station and the preference function related to operation type at each served station.

Post-production analysis approach for drone delivery fleet

This paper treats a drone delivery parcels problematic in an urban area. The civil application of drone has been developed during these last decades especially drone delivery applications. In this paper, we focus on drone delivery application in the urban area for last-mile parcel delivery. The new issue is not only the drone design but also the logistics support of a massive fleet of drones with a mission to deliver parcels in a dense urban area. We hereby treat problematic by focusing on Logistics Support System. In this context, the commercialized drone is a considered as a system on the shelf. we propose a Post-Production Logistics Support Analysis to cover the exploitation phase of a drone delivery operator.

Logistics Support Approach for Drone Delivery Fleet

This paper treats a drone delivery parcel’s problem in an urban area. Drone delivery has emerged as a potential way in the immediate future to deliver parcels in the urban area, especially in last-mile delivery. This new configuration of parcel delivery highlights the improvement of the application of Unmanned Aircraft Vehicles in the civil use. The future challenge underlying this application is not so much the design of drones for parcel delivery, but the logistics support of a massive fleet of drones with a mission to deliver at least hundreds of parcels a day in a dense urban area. We hereby treat this issue by focusing on Logistics Support System. In this paper, we propose a Post-Production Logistics Support Analysis to cover the exploitation phase of a drone delivery operator.

Disassembly scheduling using stochastic algorithms

Abstract An essential criterion for a disassembly system is the benefit it brings, that is the revenue brought by the retrieved parts and material, decreased by the cost of their retrieval. In the recycling industry the main problem is the uncertainty that occurs during the disassembly operations. A fast scheduling algorithm is proposed so as to optimize the income flow of the disassembly system taking into account alternative destructive operations. Two examples from industry are given.

Selecting configuration of reverse logistics network using sustainability indicators

The network of the reverse logistics (RL) aims to treat and re-inject into the supply chain all that can be valorized from products which are defective, at the end of life, at the end of warranty, at high obsolescence level, etc. The design of that network must take into account many things like the uncertainty about the expected volumes of these products, the forecast of consumer needs customers, producers returns projections, recycling systems, etc. In general, products are not always accompanied with complete data. Those data are often imprecise, hypothetical, inconsistent ... Our literature review is interested mainly in economic viability of an RL organization for a family of products in the context of uncertainty. It shows that almost all research papers do not take into account the incompleteness of the data, do not capitalize on the practices and the historical data of the network and, then, do not consider any indicator of sustainable development (SD). In this paper, we develop a model to select the best reverse logistic network under uncertainty of products returns. This model uses mathematic model and Bayesian network to detect the distribution of used product, integrated in Arena Software to simulate different configurations.

Performance Study for a Sustainable Strategy: Case of Electrical and Electronic Equipments Waste

Wastes of the Electrical and the Electronic Equipments (WEEE) have been a major danger because of their hazardous composition to the environment and to the human health. Today, their valorization within a reverse supply chain is a reality and it is a good thing. However, stakeholders are often divided on the issue and their positions and decisions about performance enhancement are sometimes ambiguous. A new strategy should look for collective decisions for improving performance considering the sustainable criteria of the economic, the environmental and the social aspects. It became necessary to develop an interactive decision making that considers the conflicting opinion to select the best compromise strategy. Nevertheless, ambiguity and collaboration decision modalities of different decision-makers are not considered in the real case. In this paper, a compromising strategy has been undertaking using an entropic analyze, ambiguity notions and cooperative theory. The proposed model has been applied in a Tunisian industry of Wastes of the Electric and the Electronic Equipment (WEEE).

Dynamic Bayesian Network Approach to Improve the Preventive Maintenance of Multi-State Systems

Abstract This work includes a part of the results of I.W.Soro on performance evaluation of Multi-State Systems (MSS) about the preventive maintenance policy. It was to assess the availability and the rate of production of a multi-state system based on a rate of transitions in the level of β degradation. The formalism of calculation based on Markov chains used and Chapman-Kolmogorov equations induce as many calculations as possible cases of β transition rates to deduce the one that brings the best drift of the availability curves and production rates. Moreover, the representation of multi-state system by a Markov graph quickly becomes dense and difficult to use. In this paper, it will first be presented formalization of the transition process of multi-state system (MSS) by Bayesian Networks (especially compact) and the rules governing promotion from the Markov graph. In a second step, it will be exhibited, the cost function of preventive maintenance and the best method for identifying the β transition rates and thus the best preventive maintenance policy to adopt. The optimization has done by reinforcement learning.

Performance Management of Industrial Supplies by Bayesian Networks: Proposed Approach and Industrial Application

Abstract In this paper, we present an approach to carry out an analysis of the performance of given industrial supplies or of a group of machines. This approach defines a target group for machines whose unavailability can indeed seriously hinder the objectives of production, and generates high maintenance costs. We will refer to the data of maintenance to identify the major failures and to classify relevant causes. The Bayesian networks have been used to better grasp the causes of failures and to quantify unavailability related to with these failures.