This paper introduces a synchronized arc routing problem for snow plowing operations. In this problem, routes must be designed in such a way that street segments with two or more lanes in the same direction are plowed simultaneously by different synchronized vehicles. A mixed integer formulation and an adaptive large neighborhood search heuristic are proposed. The performance of the proposed al...

In the One-Commodity Pickup and Delivery Problem (1PDP), a single commodity type is collected from a set of pickup customers to be delivered to a set of delivery customers, and the origins and destinations of the goods are not paired. We introduce a new adaptive hybrid VNS/SA (Variable Neighborhood Search/Simulated Annealing) approach for solving the 1-PDP. We perform sequences of VNS runs, whe...

To solve problems with Local Search procedures, neighborhoods have to be defined. During the resolution, a solution is typically replaced by the best solution found in its neighborhood. A question concerns the size of the neighborhood. If a small neighborhood can be explored in polynomial time, a large neighborhood search may bring a faster convergence to a local optimum of good quality (see [1...

This paper presents a Large Neighborhood Search (LNS) approach based on constraint programming to solve cumulative scheduling problems. It extends earlier work on constraint-based randomized LNS for disjunctive scheduling as reported in (Nuijten & Le Pape 1998). A breakthrough development in generalizing that approach toward cumulative scheduling lies in the presented way of calculating a parti...

Liquefied Natural Gas (LNG) is steadily becoming a common mode for commercializing natural gas. Due to the capital intensive nature of LNG projects, the optimal design of LNG supply chains is extremely important from a profitability perspective. Motivated by the need for a model that can assist in the design analysis of LNG supply chains, we address an LNG inventory routing problem where optimi...

Many optimization problems of practical interest are computationally intractable. Therefore, a practical approach for solving such problems is to employ heuristic (approximation) algorithms that can find nearly optimal solutions within a reasonable amount of computation time. An improvement algorithm generally starts with a feasible solution and iteratively tries to obtain a better solution. Ne...

The field of Distributed Constraint Optimization has gained momentum in recent years, thanks to its ability to address various applications related to multi-agent cooperation. Nevertheless, solving Distributed Constraint Optimization Problems (DCOPs) optimally is NP-hard. Therefore, in large-scale, complex applications, incomplete DCOP algorithms are necessary. Current incomplete DCOP algorithm...

The average age of the population has grown steadily in recent decades along with number people suffering from chronic diseases and asking for treatments. Hospital care is expensive often unsafe, especially older individuals. This particularly true during pandemics as SARS-CoV-2. Hospitalization at home become a valuable alternative to face efficiently huge increase treatment requests while gua...