Integer programming formulations of discrete hub location problems

The vehicle routing problem with simultaneous deliveries and pickups (VRPSDP) has attracted much research interest because of the potential to provide cost savings to transportation and logistics operators. Several extensions of VRPSDP exist. Of these extensions, the simultaneous deliveries and pickups with split loads problem (SDPSLP) has been proposed to eliminate vehicle capacity constraints, as well as allow the deliveries or pickups for a customer to be split into multiple visits. Although delivery and pickup activities are often constrained by time windows, few studies have considered such constraints when SDPSLP has been addressed. To fill the gap, this paper formulates the vehicle routing problem of simultaneous deliveries and pickups with split loads and time windows (VRPSDPSLTW) as a mixed-integer programming problem. A hybrid heuristic algorithm was developed to solve this problem. Solomon data sets with minor modifications were applied to test the effectiveness of the solution algorithm. The r...

Vehicle Routing Problem: Simultaneous Deliveries and Pickups with Split Loads and Time Windows

This paper presents a global review of the crucial strategic and tactical steps of transit planning: the design and scheduling of the network. These steps influence directly the quality of service through coverage and directness concerns but also the economic profitability of the system since operational costs are highly dependent on the network structure. We first exhibit the context and the goals of strategic and tactical transit planning. We then establish a terminology proposal in order to name sub-problems and thereby structure the review. Then, we propose a classification of 69 approaches dealing with the design, frequencies setting, timetabling of transit lines and their combinations. We provide a descriptive analysis of each work so as to highlight their main characteristics in the frame of a two-fold classification referencing both the problem tackled and the solution method used. Finally, we expose recent context evolutions and identify some trends for future research. This paper aims to contribute to unification of the field and constitutes a useful complement to the few existing reviews.

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Transit network design and scheduling: A global review

A survey of recent research on location-routing problems

Two-echelon multiple-vehicle location-routing problem with time windows for optimization of sustainable supply chain network of perishable food

A simulated annealing heuristic for the capacitated location routing problem

A multiple ant colony optimization algorithm for the capacitated location routing problem

The berth allocation is one of the major container port optimization problems. In both port operator's and ocean carriers' perspective, the minimization of the time a ship at the berth may be considered as an objective with respect to port operations. This paper focuses on the discrete and dynamic berth allocation problem (BAP), which assigns ships to discrete berth positions and minimizes the total waiting times and handling times for all ships. We formulate a mixed integer programming (MIP) model for the BAP. Since BAP is a NP-hard problem, exact solution approaches cannot solve the instances of realistic size optimally within reasonable time. We propose a particle swarm optimization (PSO) approach to solve the BAP. The proposed PSO is tested with two sets of benchmark instances in different sizes from the literature. Experimental results show that the PSO algorithm is better than the other compared algorithms in terms of solution quality and computation time.

Particle swarm optimization algorithm for the berth allocation problem

The facility location problems have been applied extensively in practice. We describe a Multiple Ant Colony System (MACS) to solve the Single Source Capacitated Facility Location Problem (SSCFLP). Lagrangian heuristics have been shown to produce good solutions for the SSCFLP. A hybrid algorithm, which combines Lagrangian heuristic and Ant Colony System (ACS), LH–ACS, is developed for the SSCFLP. The performance of the proposed methods are tested on two sets of benchmark instances and compared with other heuristic algorithms in the literature. The computational results indicate that both MACS and LH–ACS are effective and efficient for the SSCFLP and competitive with other well-known algorithms.

Combining Lagrangian heuristic and Ant Colony System to solve the Single Source Capacitated Facility Location Problem

The timed transfer concept, which seeks to schedule vehicles from various routes to arrive at some transfer stations simultaneously (or nearly so), can significantly improve service quality in transit networks. It has been implemented in some cities but with insufficient efforts to optimize coordination among connecting routes. Our problem is to optimize the headways and slack times jointly for timed transfers to minimize the total costs of operating a multiple-hub transit network. In this paper, a heuristic algorithm is used to optimize the headways and slack times for all coordinated routes. Here, headways are integer multiples of a base cycle to ensure that vehicles on different routes can operate in phase and arrive nearly simultaneously at transfer stations. The results show that as demand decreases, optimized headways increase and the net benefits of coordinated operation also increase. For routes with significantly different demand or route length, coordination with integer-ratio headways is preferable to a single common headway. The sensitivity of the transit service characteristics to various demand and cost parameters is discussed. The results also show that the optimized slack times for routes vary with such variables as headways, vehicle arrival-time variance, transfer volumes, and passenger time values. For routes with high standard deviations of arrivals, it is not worth attempting schedule coordination.

Ching-Jung Ting

Papers

A simulated annealing heuristic for the capacitated location routing problem

A multiple ant colony optimization algorithm for the capacitated location routing problem

Particle swarm optimization algorithm for the berth allocation problem

Combining Lagrangian heuristic and Ant Colony System to solve the Single Source Capacitated Facility Location Problem

Schedule Coordination in a Multiple Hub Transit Network