A new algorithm based CSP framework for RFID network planning

International audienceThe huge growth of industrial society requires the deployment of radio frequency identification networks on a large scale. This necessitates the installation of a large number of radio frequency identification components (readers, tags, middleware and others). As a consequence, the cost and complexity of networks are increasing due to the large number of readers to be installed. Finding the optimal number, placement and parameters of readers to provide a high quality of service for radio frequency identification systems is a critical problem. A good planning affords a basic need for radio frequency identification networks, such as coverage, load balance and interference between readers. This problem is famous in the literature as a radio frequency identification network planning problem. All the proposed approaches in the literature have been based on meta-heuristics. In this paper, we design a new algorithm, called the RNP-CSP algorithm based on the constraint satisfaction problem framework to solve the radio frequency identification network planning problem. The performance evaluation shows that the RNP-CSP algorithm is more efficient than PS 2 O , GPSO and VNPSO-RNP

Multi-trip pickup and delivery problem, with split loads, profits and multiple time windows to model a real case problem in the constructionindustry

International audienceThis paper presents the first optimization study of multi-site transportation in the construction industry, whichallows mutualizing building material delivery and construction waste removal. This study is inspired by a real-worldproblem encountered in the framework of the French R&D project DILC, in which a pooling platformmust centralize the delivery of building materials to the construction sites and the pickup of their waste, usinga limited and heterogeneous fleet that are allowed to perform multiple trips, under time and capacity limitationconstraints. The problem under study, called the Multi-Trip Pickup and Delivery Problem, with Split loads,Profits and Multiple TimeWindows is a new extension of the vehicle routing problem with pickup and delivery,that considers new realistic constraints specific to the construction industry such as each construction site mayhave a priority on its delivery request or its pickup request or both, with a higher priority level for deliveryrequest, and each construction site may have several time windows. To solve this problem, we propose newinsertion criteria that takes into consideration several aspects of our problem, which we have embedded in aconstruction heuristic. Experiments performed on new real instances have shown the efficiency of our method

ILS-RVND Algorithm for Multi-trip Pickup and Delivery Problem, with Split Loads, Profits and Multiple Time Windows

International audienceThis paper deals with a real application encountered in the construction sector, which consists in a new variant of the pickup and delivery problem, including several constraints that have never been combined in the same variant, denoted MTPDSPTW. This problem is defined by a set of construction sites that have a delivery demand for construction materials and also a waste removal request. Each construction site has a certain profit which is computed according to the urgency of the pickup and delivery demand. Each site can be visited several times during the day, but the delivery must be done within a set of time windows specified by each site. Heterogeneous vehicles with di erent availability located at a massification and waste treatment platform must do multiple tours to serve the requests. The objective is to minimize the total travel distance and to maximise the profit. The developed method is based on the Iterated Local Search metaheuristic which uses a Random Variable Neighborhood Descent (RVND) in the Local Search Procedure. Di erent implementation schemes of the proposed method are tested on set of data instances provided by our industrial partner. The results show the e ectiveness of ILS-RVND compared to ILS with a single local search operator. ILS-RVND improves the results of the SBH heuristic by 13.15%