We study a generalization of the quadratic assignment problem (QAP) by allowing multiple equipments to be assigned at a single location as long as resources at the location permit. This problem arises in many real world applications such as facility location problem and logistics network design. We call the problem as the generalized quadratic assignment problem (GQAP) and show that this relaxa...

In this paper, dynamic facility location and supply chain planning are studied through minimizing the costs of facility location, path selection and transportation of coal under demand uncertainty. The proposed model dynamically incorporates possible changes in transportation network, facility investment costs, operating cost and changes in facility location. In addition, the time variation and...

Cloud logistics comprises the virtualization of logistics resources from different logistics service providers. Those resources are pooled, combined and encapsulated within customer-specific modular logistics services. The pooling within networks comprises a high quantity of available logistics resources and services. Domain-specific structuring with the concept of the logistics service map hel...

We consider the information theoretical capacity of the network flow watermarking problem. Finding capacity bounds of the watermarking problem can lead to compare different watermarking schemes and help in designing more efficient network flow watermarks.

Providing distributed services on road networks is an essential concern for many applications, such asmail delivery, logistics and police patrolling. Designing effective and balanced routes for these applications is challenging, especially when involving multiple postmen from distinct depots. In this research, we formulate this routing problem as a MinMaxMultiple-Depot Rural Postman Problem (MM...

In this paper we propose improved Benders decomposition schemes for solving a remanufacturing supply chain design problem (RSCP). We introduce a set of valid inequalities in order to improve the quality of the lower bound and also to accelerate the convergence of the classical Benders algorithm. We also derive quasi Pareto-optimal cuts for improving convergence and propose a Benders decompositi...

In this paper we propose some non-greedy heuristics and develop an Augmented-Neural-Network (AugNN) formulation for solving the classical open-shop scheduling problem (OSSP). AugNN is a neural network based meta-heuristic approach that allows integration of domain-specific knowledge. The OSSP is framed as a neural network with multiple layers of jobs and machines. Input, output and activation f...

This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We...