A two-phase approach for real-world train unit scheduling

A two-phase approach for the train unit scheduling problem is proposed. The first phase assigns and sequences train trips to train units temporarily ignoring some station infrastructure details. Real-world scenarios such as compatibility among traction types and banned/restricted locations and time allowances for coupling/ decoupling are considered. Its solutions would be near-operable. The second phase focuses on satisfying the remaining station detail requirements, such that the solutions would be fully operable. The first phase is modeled as an integer fixed-charge multicommodity flow (FCMF) problem. A branch-and-price approach is proposed to solve it. Experiments have shown that it is only capable of handling problem instances within about 500 train trips. The train company collaborating in this research operates over 2400 train trips on a typical weekday. Hence, a heuristic has been designed for compacting the problem instance to a much smaller size before the branch-and-price solver is applied. The process is iterative with evolving compaction based on the results from the previous iteration, thereby converging to near-optimal results. The second phase is modeled as a multidimensional matching problem with a mixed integer linear programming (MILP) formulation. A column-and-dependentrow generation method for it is under development

Enhanced exact solution methods for the Team Orienteering Problem

The Team Orienteering Problem (TOP) is one of the most investigated problems in the family of vehicle routing problems with profits. In this paper, we propose a Branch-and-Price approach to find proven optimal solutions to TOP. The pricing sub-problem is solved by a bounded bidirectional dynamic programming algorithm with decremental state space relaxation featuring a two-phase dominance rule relaxation. The new method is able to close 17 previously unsolved benchmark instances. In addition, we propose a Branch-and-Cut-and-Price approach using subset-row inequalities and show the effectiveness of these cuts in solving TOP

The Types of Tunnels Main-tenance in Umbrella Arch Method

Abstract During tunneling in loose grounds, the ground deformation caused by drillings around the tunnel, leads to land subsidence and the adjacent tunnel which would affect tunnel structure and surrounding structures. In such situations it is necessary to improve the properties of the ground prior to drilling operations. In order to acquire tunnel face stability during excavation operations in areas with loose soil fault or areas with lack of adhesion, there are various methods such as split cross drilling, frame holder or auxiliary pre-holding methods such as umbrella arch method; preholding methods must provide safety when drilling and must be affordable, economically. In this study, we assessed the previous studies on methods and behaviors of umbrella arch strategy in reinforcing the concrete tunnels, reached the purpose with experimental and numerical methods and offered the latest design achievements, implementation progresses and analysis in relation with this method

A Branch-First, Cut-Second Approach for Locomotive Assignment

The problem of assigning locomotives to trains consists of selecting the types and number of engines that minimize the fixed and operational locomotive costs resulting from providing sufficient power to pull trains on fixed schedules. The force required to pull a train is often expressed in terms of horsepower and tonnage requirements rather than in terms of number of engines. This complicates the solution process of the integer programming formulation and usually creates a large integrality gap. Furthermore, the solution of the linearly relaxed problem is strongly fractional. To obtain integer solutions, we propose a novel branch-and-cut approach. The core of the method consists of branching decisions that define on one branch the projection of the problem on a low-dimensional subspace. There, the facets of the polyhedron describing a restricted constraint set can be easily derived. We call this approach branch-first, cut-second. We first derive facets when at most two types of engines are used. We then extend the branching rule to cases involving additional locomotive types. We have conducted computational experiments using actual data from the Canadian National railway company. Simulated test-problems involving two or more locomotive types were solved over 1-, 2-, and 3-day rolling horizons. The cuts were successful in reducing the average integrality gap by 52% for the two-type case and by 34% when more than 25 types were used. Furthermore, the branch-first, cut-second approach was instrumental in improving the best known solution for an almost 2,000-leg weekly problem involving 26 locomotive types. It reduced the number of locomotives by 11, or 1.1%, at an equivalent savings of $3,000,000 per unit. Additional tests on different weekly data produced almost identical results.integer linear programming, branch and cut, decomposition, scheduling, railway