Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A passenger demand model for airline flight scheduling and fleet routing
Computers and Operations Research
Performance evaluation of acceptance probability functions for multi-objective SA
Computers and Operations Research
Solving a Time-Space Network Formulation for the Convoy Movement Problem
Operations Research
Expert Systems with Applications: An International Journal
A model and a solution algorithm for the car pooling problem with pre-matching information
Computers and Industrial Engineering
A model with a solution algorithm for the cash transportation vehicle routing and scheduling problem
Computers and Industrial Engineering
A Single-Objective Recovery Phase Model
International Journal of Information Technology Project Management
Humanitarian/emergency logistics models: a state of the art overview
Proceedings of the 2013 Summer Computer Simulation Conference
Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling
Expert Systems with Applications: An International Journal
Logistical support scheduling under stochastic travel times given an emergency repair work schedule
Computers and Industrial Engineering
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Emergency roadway repair and relief distribution planning following a natural disaster has traditionally been done manually and separately, based on the decision-maker's experience, disregarding the interrelationship between emergency roadway repair and relief distribution from the system perspective, which may yield inferior solutions. Hence, in this research we consider minimizing the length of time required for both emergency roadway repair and relief distribution, as well as the related operating constraints, to develop a model, for planning emergency repair and relief distribution routes and schedules within a limited time. We construct a time-space network for emergency repair and another for relief distribution. A number of operational constraints are set between these two networks according to real constraints. Our model is a multi-objective, mixed-integer, multiple-commodity network flow problem. We adopt the weighting method and develop a heuristic to efficiently solve this problem in practice. To evaluate our model and the solution algorithm, we perform a case study. The results show the model and the solution algorithm could be useful in practice.