A survey of models and algorithms for winter road maintenance. Part II: system design for snow disposal

This is the second part of a four-part survey of optimization models and solution algorithms for winter road maintenance planning. The first part addresses system design problems for spreading and plowing operations. The aim of this paper is to provide a comprehensive survey of optimization models and solution methodologies for the design of systems for snow disposal operations. These problems include partitioning a region or road network into sectors, locating snow disposal sites, allocating sectors to snow disposal sites, and allocating sectors to private companies or governmental agencies. The two last parts of the survey mainly concentrate on vehicle routing for winter road maintenance.     

A survey of models and algorithms for winter road maintenance. Part I: system design for spreading and plowing

Winter road maintenance operations involve a host of decision-making problems at the strategic, tactical, operational, and real-time levels. Those operations include spreading of chemicals and abrasives, snow plowing, loading snow into trucks, and hauling snow to disposal sites. As the first of a four-part survey, this paper reviews optimization models and solution algorithms for the design of winter road maintenance systems for spreading and plowing operations. System design problems for snow disposal operations are discussed in the second paper. The two last parts of the survey mainly address vehicle routing, depot location, and fleet sizing models for winter road maintenance. The present paper surveys research on determining the level of service policy and partitioning a region or road network into sectors for spreading and plowing operations. We also describe the applied setting in which these problems arise.     

Synchronized arc routing for snow plowing operations

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 algorithm is evaluated over a large instance set, including artificial and real data. Computational results confirm the efficiency of the algorithm.     

A survey of models and algorithms for emergency response logistics in electric distribution systems. Part II: Contingency planning level

This is the second part of a two-part survey of optimization models and solution algorithms for emergency response planning in electric distribution systems. The first part of the survey addresses reliability planning problems with fault considerations related to electric distribution operations. The aim of this second part is to provide a comprehensive survey of optimization models and solution methodologies for contingency planning problems related to electric distribution operations. These problems include the restoration of service, the sequencing of switching operations, the routing of repair vehicles, the scheduling of repair crews, and the assignment of crews to repair sites.     

A survey of models and algorithms for emergency response logistics in electric distribution systems. Part I: Reliability planning with fault considerations

Emergency response operations in electric distribution systems involve a host of decision-making problems at the reliability and contingency planning levels. Those operations include fault diagnosis, fault location, fault isolation, restoration, and repair. As the first of a two-part survey, this paper reviews optimization models and solution methodologies for reliability planning problems with fault considerations related to electric distribution operations. Contingency planning problems of emergency distribution response are discussed in the second part. The present paper surveys research on determining a distribution substation single-fault capacity, reallocating excess load, configuring distribution systems, partitioning a geographical area into service territories, and locating material stores and depots.