1,721,005 research outputs found
Evaluation of the flow of goods at a warehouse logistic department by Petri Nets
No full textThis paper addresses the analysis issue of the complex interactions arising among different components of a warehouse logistic system. In particular, the focus is on a case study related to the handling operations required by the flow of goods within a store of Ikea, located in the center of Italy. The proposed study has been performed using Petri Nets (PNs) as discrete event modelling and simulation framework. In particular, this paper aims to bring out the innovative aspect of the use of PNs as tools to support the functional specifications of warehouse systems, highlighting their strengths and weakness. The goal is to emphasize critical factors in the entire logistic chain within the store and suggest solutions for improving its efficiency. In this regards, PNs have been proved to be quite suitable to easily represent the main features of the departments under consideration, showing at the same time the main logistic processes in which both labor and equipment are involved. The dynamics of the considered logistic system is evaluated, focusing on the three main operating cycles implemented at the Ikea store under consideration. Further, simulating directly the PN model, along with a quantitative analysis, has been possible to identify delays in the complete logistic chain and determine performance indices, such as utilization rate of the resources. Suggestions for improving the productivity of the system are given
Operations management in distribution networks within a smart city framework
No full textThis article studies a vehicle routing problem with environmental constraints that are motivated by the requirements for sustainable urban transport. The empirical research presents a fleet planning problem that takes into consideration both minimum cost vehicle routes and minimum pollution. The problem is formulated as a mixed integer linear programming model and experimentally validated using data collected from a real situation: a grocery company delivering goods ordered via e-channels to customers spread in the urban and metropolitan area of Genoa smart city. The proposed model is a variant of the vehicle routing problem tailored to include environmental issues and street limitations. Its novelty regards also the use of real data instances provided by the B2C grocery company. Managerial implications are the choice of both the routes and the number and type of vehicles. Results show that commercial distribution strategies achieve better results in term of both business and environmental performance, provided the smart mobility goals and constraints are included into the distribution model from the beginning
Grocery distribution plans in urban networks with street crossing penalties
No full textFollowing the emergency caused by the Covid-19 pandemic, there is the need, among other measures, to modify urban mobility plans in order to reduce the use of collective public transport, reducing the crowding of people while also preventing traffic congestion through discouraging the use of private vehicles. From this perspective, retail companies operating within cities must also reorganize themselves, considering both the unpredictable requirements of environmental sustainability and the new mobility needs calling for the promotion of bicycles and electric scooters. In this context, we deal with the need to determine minimum cost routes in urban areas for delivering orders placed through e-channels. More precisely, we face a variant of the green vehicle routing problem of heterogeneous fleets, in which the objective function includes environmental impact cost components that differ by vehicle type. Moreover, as a novel issue, attention must be paid to avoid crossing and passing close to bicycle lanes; therefore, penalties are associated with the transit of vehicles near bicycle lanes. To address this problem, we propose a mixed integer linear programming model and a matheuristic associated with it. The proposed approach is then used to analyze different scenarios derived from the transportation network of the city of Milan, Italy. Milan is one of the smartest cities in Europe from the mobility point of view but also one of the most affected by the Covid-19 pandemic, and the municipality is making a big investment to promote the use of bicycles
Min-cost route problems for multimodal sustainable logistics cooperation
No full textThis article addresses the pressing need for sustainable logistics practices in light of the current global climate emergency. Specifically, we tackle the problem of defining the shortest routes for various carriers in a multimodal logistics network while simultaneously reducing environmental impact. A novel aspect of our approach is that each transport demand from origin to destination is satisfied by considering all the routes within the multimodal network that intersect with the path associated with the transportation request. The primary goal is to minimise the number of circulating vehicles by fully utilising their available cargo capacity. To achieve this, we propose a mixed-integer linear programming model based on a multimodal graph. The objective function comprises various cost components, taking into account the transportation and service costs of different vehicle types (trucks, trains, ships, and aeroplanes). Additionally, the search for the optimal solution incorporates several parameters aligned with the paradigm of cooperative logistics and environmental sustainability. Specifically, pollutant emissions and payload utilisation are factored in through specifically tailored cost coefficients. A total of 3,240 test instances, derived from routes within the Italian multimodal transportation network, were generated and solved to optimality. The results underscore the effectiveness of the proposed model in addressing the aforementioned environmental concerns
A Constructive Heuristics and an Iterated Neighborhood Search Procedure to Solve the Cost-Balanced Path Problem
No full textThis paper presents a new heuristic algorithm tailored to solve large instances of an NP-hard variant of the shortest path problem, denoted the cost-balanced path problem, recently proposed in the literature. The problem consists in finding the origin–destination path in a direct graph, having both negative and positive weights associated with the arcs, such that the total sum of the weights of the selected arcs is as close to zero as possible. At least to the authors’ knowledge, there are no solution algorithms for facing this problem. The proposed algorithm integrates a constructive procedure and an improvement procedure, and it is validated thanks to the implementation of an iterated neighborhood search procedure. The reported numerical experimentation shows that the proposed algorithm is computationally very efficient. In particular, the proposed algorithm is most suitable in the case of large instances where it is possible to prove the existence of a perfectly balanced path and thus the optimality of the solution by finding a good percentage of optimal solutions in negligible computational time
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