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The problem of the optimal three-level location allocation of transfer center, processing factory and distribution center for supply chain network under uncertain transportation cost and customer demand are studied. We establish a two-stage fuzzy 0-1 mixed integer optimization model, by considering the uncertainty of the supply chain. Given the complexity of the model, this paper proposes a modified hybrid second order particle swarm optimization algorithm (MHSO-PSO) to solve the resulting model, yielding the optimal location and maximal expected return of supply chain simultaneously. A case study of clothing supply chain in Shanghai of China is then presented to investigate the specific influence of uncertainties on the transfer center, clothing factory and distribution center three-level location. Moreover, we compare the MHSO-PSO with hybrid particle swarm optimization algorithm and hybrid genetic algorithm, to validate the proposed algorithm based on the computational time and the convergence rate. [ABSTRACT FROM AUTHOR]

Waste sorting is an imperative and significant issue in China, of which sorted-waste collection and transportation are indispensable parts. Despite its vital yet practical significance, few studies research mathematical models or algorithms of waste collection and transportation from the perspective of waste sorting. To address this issue, we extend a novel transportation model for the waste management system, namely, capacitated location routing problem with queuing time (CLRPQT) and design a cross-entropy and simulated-annealing based hyper-heuristic algorithm (CE-SAHH) for it. The main idea of this paper is three-fold: (1) As a particular property of this problem, source nodes cannot but need to be served by more than one vehicle that causes queuing time between a heterogeneous fleet of vehicles, which is novel in terms of the proposed model; (2) For the methodological contribution, a character encoding scheme, new decoding procedure, and local search strategy are designed embedded in the proposed method; (3) An integration of simulated annealing strategy and the cross-entropy-based hyper-heuristic algorithm is developed to overcome the combinatorial optimization problem with a more complex solution of this study. Finally, the results and analysis of three numeric experiments on benchmark datasets, new instances of CLRPQT, and simulation data in Shanghai, China, verify the effectiveness and universality of the proposed model and method. • A novel model with interactional routes for sorted-waste transportation is proposed. • A cross-entropy-based hyper-heuristic algorithm is proposed and performs well. • The novel model and method based on sorted waste enrich the waste management system. • Real-life data is used to verify the method and some managerial insights are drawn. [ABSTRACT FROM AUTHOR]

Vehicle-based sensors can be used for traffic monitoring. These sensors are usually set with long sampling intervals to save communication costs and to avoid network congestion. In this paper, we are interested in understanding the traffic-monitoring performance that we can expect from such vehicle-based mobile sensor networks, despite the incomplete information provided. This is a fundamental problem to be addressed. A performance evaluation has been carried out in Shanghai, China, by utilizing the vehicle-based sensors installed in about 4000 taxies. Two types of traffic status-estimation algorithms, i.e., the link-based and the vehicle-based, are introduced and analyzed. The results show that estimations of the traffic status based on these imperfect data are reasonably accurate. Therefore, the feasibility of such an application is demonstrated. [ABSTRACT FROM AUTHOR]

Purpose - Taking into account the long-term influences of the non-linear behavior of the material as well as the large deformation and contact conditions, the limiting factors of the computer simulation are the computer runtime and the memory requirement during solution of seismic response analysis for immersed tunnel. This research aims to overcome these problems. Design/methodology/approach - This research deals with parallel explicit finite element simulation with domain decomposition for seismic response analysis of immersed tunnel, which is the non-linear and time-dependent behavior of complex structures in engineering. A domain decomposition method based on parallel contact algorithm and dynamic-explicit time integration procedure are used, and the latter is used for the solution of the semi-discrete equations of motion, which is very suited for parallel processing. Using the high performance computer SGI Onyx3800, the seismic response analysis of the immersed tunnel in Shanghai is processed with more than 1.2 million nodes and more than 1 million elements in final finite element model. Findings - The results show numerical scalability of this algorithm and reveal the dangerous joints in this immersed tunnel under Tangshan seismic acceleration, and it could also provide references for the antiseismic design of the immersed tunnel. Originality/value - With the increasing demands in the scale, accuracy and speed of numerical simulation in geotechnical engineering, parallel computing has its great application in this area. This paper fulfils an identified method need, and it is believed more and more research work will be devoted to this research field in the near future. [ABSTRACT FROM AUTHOR]