scholarly journals A Simulated Annealing Algorithm for Intermodal Transportation on Incomplete Networks

2021 ◽  
Vol 11 (10) ◽  
pp. 4467
Author(s):  
Mustapha Oudani

Growing competition in the world enforces the need for an efficient design of transportation networks. Furthermore, a competitive transportation network should also be eco-friendly. As road transportation is responsible for the largest quantities of CO2 emissions, Intermodal Transportation (IT) might be a potential alternative. From this perspective, intermodal terminals location is a cornerstone for building a sustainable transportation network. The purpose of this paper is to study and efficiently solve the Intermodal Terminal Location Problem on incomplete networks. We model this problem as a mixed integer linear program and develop a simulated annealing algorithm to tackle medium and large instances. The computational results show that the obtained solutions using simulated annealing are competitive and close to the exact solutions found by CPLEX solver for small and medium instances. The same developed algorithm outperforms the best found solutions from the literature using heuristics for larger instances.

Transport ◽  
2011 ◽  
Vol 26 (2) ◽  
pp. 133-140 ◽  
Author(s):  
Arash Jahangiri ◽  
Shahriar Afandizadeh ◽  
Navid Kalantari

In recent years, natural and man-made disasters have increased and consequently put people's lives in danger more than before. Some of the crises are predictable. In these cases, there is a limited time for effective respond minimizing fatalities when people should be evacuated in a short time. Therefore, a transportation network plays a key role in evacuation. Hence, the outbound paths of urban networks are not sufficient from the viewpoint of number and capacity to encounter a huge amount of people; furthermore, it is costly to construct new routes or increase the capacity of the existing ones. Thus, a better utilization of the existing infrastructure should be considered. The article presents a model that determines optimum signal timing and increases the outbound capacity of the network. Moreover, in regard for the magnitude of the problem, an optimal solution could not be reached employing ordinary methods; therefore, the simulated annealing algorithm which is a meta-heuristic technique is used. The results of this study demonstrated that the objective function of the problem was greatly improved. Santrauka Pastaruoju metu gamtos ir žmonijos sukeltų nelaimių padaugėjo, todėl susiduriama su daugiau pavojų nei anksčiau. Kai kurių krizių ir nelaimių negalima numatyti. Tokiais atvejais veiksmingas reagavimo laikas yra ribotas, bet padeda sumažinti mirties atvejų, greitai evakuojant žmones. Šiuo atveju ypač svarbus yra transporto tinklas ir transportavimas. Iš miesto į užmiestį vedančios gatvės nėra pakankamai efektyvios, norint pervežti didelį žmonių skaičių. Be to, brangu pradėti rengti naujus maršrutus arba didinti jau esančių gatvių pralaidumą. Todėl turėtų būti apsvarstytas geresnis esančios transporto infrastruktūros panaudojimas. Straipsnyje nagrinėjamas modelis, nulemiantis optimalų šviesoforo signalo laiko nustatymą ir padidinantis išvykstančiųjų skaičių. Atsižvelgiant į problemos svarbą, optimalus sprendimas negali būti priimtas, naudojant įprastus metodus. Todėl naudojamas metaeuristinis metodas – modeliuojamasis atkaitinimo algoritmas (simulated annealing algorithm). Šio darbo rezultatai rodo, kad problemos tikslo funkcija labai pagerėjo. Резюме В настоящее время в мире увеличилось число стихийных бедствий и бедствий, связанных с неосторожной деятельностью людей. Значительную часть бедствий предсказать невозможно. В таких случаях эффективное время реагирования ограничено, что в свою очередь помогает уменьшить количество смертельных исходов и несчастных случаев при эвакуации населения. В этом случае транспортная сеть и сам процесс транспортирования играют решающую роль. Улицы, ведущие из города, становятся неэффективными из-за огромного количества людей. Кроме того, подготовка новых маршрутов или увеличение пропускной способности имеющихся улиц являются дорогостоящими мероприятиями. Поэтому следует проанализировать возможности более эффективного использования уже имеющейся транспортной инфраструктуры. В статье представлена модель, позволяющая определить выбор и установить оптимальное время сигнала светофора во время аварийной эвакуации с целью увеличить число эвакуируемых. Учитывая важность проблемы, оптимальное решение не может быть принято с использованием обычных методов. Поэтому используется метаэвристический метод – алгоритм имитации отжига (simulated annealing algorithm). Результаты, представленные в исследовании, показали, что целевая функция исследуемой проблемы значительно улучшилась


2020 ◽  
Vol 2020 ◽  
pp. 1-21 ◽  
Author(s):  
Yan Sun

In this study, the author focuses on modeling and optimizing a freight routing problem in a road-rail intermodal transportation network that combines the hub-and-spoke and point-to-point structures. The operations of road transportation are time flexible, while rail transportation has fixed departure times. The reliability of the routing is improved by modeling the uncertainty of the road-rail intermodal transportation network. Parameters that are influenced by the real-time status of the network, including capacities, travel times, loading and unloading times, and container trains’ fixed departure times, are considered uncertain in the routing decision-making. Based on fuzzy set theory, triangular fuzzy numbers are employed to formulate the uncertain parameters as well as resulting uncertain variables. Green routing is also discussed by treating the minimization of carbon dioxide emissions as an objective. First of all, a multiobjective fuzzy mixed integer nonlinear programming model is established for the specific reliable and green routing problem. Then, defuzzification, linearization, and weighted sum method are implemented to present a crisp linear model whose global optimum solutions can be effectively obtained by the exact solution algorithm run by mathematical programming software. Finally, a numerical case is given to demonstrate how the proposed methods work. In the case, sensitivity analysis is adopted to reveal the effects of uncertainty on the routing optimization. Fuzzy simulation is then performed to help decision makers to select the best crisp route plan by determining the best confidence level shown in the fuzzy chance constraints.


2021 ◽  
pp. 1-23
Author(s):  
Junxiang Xu ◽  
Jingni Guo ◽  
Yongdong Sun ◽  
Qiuyu Tang ◽  
Jin Zhang

We not only firstly applied the theory of hub-and-spoke network to the field of integrated transportation network planning, but also combined our proposed method with Sichuan-Tibet railway, one of super large projects in China, to discuss the optimization and the layout of hub-and-spoke integrated transportation network along the Sichuan-Tibet railway after it is put into operation in the future and put forward some directional policy recommendations. In our study, we have made clear the topological structure of the multi hub and single allocation hybrid hub-and-spoke integrated transportation network in the passenger transportation corridors, established the integer programming model aiming at the minimum generalized travel cost in the network, and we designed the simulated annealing algorithm to solve this problem. In the empirical study, we find that if 5 nodes are selected as hub nodes in hub-and-spoke integrated transportation network, the generalized cost of network travel will be minimized and these specific location of 5 hub nodes can be determined by the selecting principle of hub nodes location, which we proposed in our study. The simulated annealing algorithm can help us to find the connection relationship between nodes. Then we can achieve three types of hub-and-spoke integrated transportation network layout patterns with railway, highway and aviation as the hub nodes. Though further comparative analysis, we find that it is more feasible to choose the integrated transportation network with railway nodes as the hub in transportation organization. Based on this understanding, we put forward policy recommendations on transportation organization to support high-quality planning and operation of integrated transportation network to Sichuan Tibet region in China in the future.


2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Wucheng Yang ◽  
Wenming Cheng

Multi-manned assembly lines have been widely applied to the industrial production, especially for large-sized products such as cars, buses, and trucks, in which more than one operator in the same station simultaneously performs different tasks in parallel. This study deals with a multi-manned assembly line balancing problem by simultaneously considering the forward and backward sequence-dependent setup time (MALBPS). A mixed-integer programming is established to characterize the problem. Besides, a simulated annealing algorithm is also proposed to solve it. To validate the performance of the proposed approaches, a set of benchmark instances are tested and the lower bound of the proposed problem is also given. The results demonstrated that the proposed algorithm is quite effective to solve the problem.


2018 ◽  
Vol 52 (4-5) ◽  
pp. 1245-1260 ◽  
Author(s):  
Alireza Eydi ◽  
Javad Mohebi

Facility location is a critical component of strategic planning for public and private firms. Due to high cost of facility location, making decisions for such a problem has become an important issue which have gained a large deal of attention from researchers. This study examined the gradual maximal covering location problem with variable radius over multiple time periods. In gradual covering location problem, it is assumed that full coverage is replaced by a coverage function, so that increasing the distance from the facility decreases the amount of demand coverage. In variable radius covering problems, however, each facility is considered to have a fixed cost along with a variable cost which has a direct impact on the coverage radius. In real-world problems, since demand may change over time, necessitating relocation of the facilities, the problem can be formulated over multiple time periods. In this study, a mixed integer programming model was presented in which not only facility capacity was considered, but also two objectives were followed: coverage maximization and relocation cost minimization. A metaheuristic algorithm was presented to solve the maximal covering location problem. A simulated annealing algorithm was proposed, with its results presented. Computational results and comparisons demonstrated good performance of the simulated annealing algorithm.


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