Hazmats Transportation Network Design Model with Emergency Response under Complex Fuzzy Environment

A bilevel optimization model for a hazardous materials transportation network design is presented which considers an emergency response teams location problem. On the upper level, the authority designs the transportation network to minimize total transportation risk. On the lower level, the carriers first choose their routes so that the total transportation cost is minimized. Then, the emergency response department locates their emergency service units so as to maximize the total weighted arc length covered. In contrast to prior studies, the uncertainty associated with transportation risk has been explicitly considered in the objective function of our mathematical model. Specifically, our research uses a complex fuzzy variable to model transportation risk. An improved artificial bee colony algorithm with priority-based encoding is also applied to search for the optimal solution to the bilevel model. Finally, the efficiency of the proposed model and algorithm is evaluated using a practical case and various computing attributes

On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

Cargo Consolidation and Distribution Through a Terminals-Network: A Branch-And-Price Approach

Less-than-truckload is a transport modality that includes many practical variations to convey a number of transportation-requests from the origin locations to their destinations by using the possibility of goods-transshipments on the carrier?s terminals-network. In this way logistics companies are required to consolidate shipments from different suppliers in the outbound vehicles at a terminal of the network. We present a methodology for finding near-optimal solutions to a less-than-truckload shipping modality used for cargo consolidation and distribution through a terminals-network. The methodology uses column generation combined with an incomplete branch-and-price procedure.Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

An Alternative Fuel Refueling Station Location Model considering Detour Traffic Flows on a Highway Road System

With the development of alternative fuel (AF) vehicle technologies, studies on finding the potential location of AF refueling stations in transportation networks have received considerable attention. Due to the strong limited driving range, AF vehicles for long-distance intercity trips may require multiple refueling stops at different locations on the way to their destination, which makes the AF refueling station location problem more challenging. In this paper, we consider that AF vehicles requiring multiple refueling stops at different locations during their long-distance intercity trips are capable of making detours from their preplanned paths and selecting return paths that may be different from original paths for their round trips whenever AF refueling stations are not available along the preplanned paths. These options mostly need to be considered when an AF refueling infrastructure is not fully developed on a highway system. To this end, we first propose an algorithm to generate alternative paths that may provide the multiple AF refueling stops between all origin/destination (OD) vertices. Then, a new mixed-integer programming model is proposed to locate AF refueling stations within a preselected set of candidate sites on a directed transportation network by maximizing the coverage of traffic flows along multiple paths. We first test our mathematical model with the proposed algorithm on a classical 25-vertex network with 25 candidate sites through various scenarios that consider a different number of paths for each OD pair, deviation factors, and limited driving ranges of vehicles. Then, we apply our proposed model to locate liquefied natural gas refueling stations in the state of Pennsylvania considering the construction budget. Our results show that the number of alternative paths and deviation distance available significantly affect the coverage of traffic flows at the stations as well as computational time