Emergency Medical Services (EMS) play a crucial role in healthcare systems, managing pre-hospital or out-of-hospital emergencies from the onset of an emergency call to the patient’s arrival at a healthcare facility. The design of an efficient ambulance location model is pivotal in enhancing survival rates, controlling morbidity, and preventing disability. Key factors in the classical models typically include travel time, demand zones, and the number of stations. While urban EMS systems have received extensive examination due to their centralized populations, rural areas pose distinct challenges. These include lower population density and longer response distances, contributing to a higher fatality rate due to sparse population distribution, limited EMS stations, and extended travel times. To address these challenges, we introduce a novel mathematical model that aims to optimize coverage and equity. A distinctive feature of our model is the integration of equity within the objective function, coupled with a focus on practical response time that includes the period required for personal protective equipment procedures, ensuring the model’s applicability and realism in emergency response scenarios. We tackle the proposed problem using a tailored genetic algorithm and propose a greedy algorithm for solution construction. The implementation of our tailored Genetic Algorithm promises efficient and effective EMS solutions, potentially enhancing emergency care and health outcomes in rural communities.

This paper proposes a Petri net based mathematical programming approach to combinatorial optimization, in which we generate integer linear programming problems from Petri net models instead of the direct mathematical formulation. We treat two types of combinatorial optimization problems, ordinary problems and time-dependent problems. Firstly, we present autonomous Petri net modeling for ordinary optimization problems, where we obtain fundamental constraints derived from Petri net properties and additional problem-specific ones. Secondly, we propose a colored timed Petri net modeling approach to time-dependent problems, where we generate variables and constraints for time management and for resolving conflicts. Our Petri net approach can drastically reduce the difficulty of the mathematical formulation in a sense that (1) the Petri net modeling does not require deep knowledge of mathematical programming and technique of integer linear model formulations, (2) our automatic formulation allows us to generate large size of integer linear programming problems, and (3) the Petri net modeling approach is flexible for input parameter changes of the original problem.

A new algorithm is proposed for finding all solutions of piecewise-linear resistive circuits using separable programming. In this algorithm, the problem of finding all solutions is formulated as a separable programming problem, and it is solved by the modified simplex method using the restricted-basis entry rule. Since the modified simplex method finds one solution per application, the proposed algorithm can find all solutions efficiently. Numerical examples are given to confirm the effectiveness of the proposed algorithm.

We use the network utility maximization (NUM) framework to create an efficient and fair medium access control (MAC) protocol for wireless networks. By adjusting the parameters in the utility objective functions of NUM problems, we control the tradeoff between efficiency and fairness of radio resource allocation through a rigorous and systematic design. In this paper, we propose a scheduling-based MAC protocol. Since it provides an upper-bound on the achievable performance, it establishes the optimality benchmarks for comparison with other algorithms in related work.

The optical network represents a promising approach to achieve a scalable backbone network. In backbone networks, survivability is important because high volumes of traffic are prone to be damaged by faulty equipment. Various design methods for survivable optical networks have been proposed, although none considering the simultaneous maintenance of multiple transmission lines has been proposed to our knowledge. This paper proposes a design method for survivable optical networks where multiple transmission lines sharing common transmission equipment may suffer simultaneous damage, due to failure in the transmission equipment. Moreover, two transmission lines can be maintained simultaneously. A mathematical programming model to obtain the optimum lightpath arrangement is presented assuming three kinds of lightpath recovery schemes. The relation between the required transmission line capacity and the combination pattern of two transmission lines that undergo maintenance is clarified using the proposed design method.

Integration of the IP/MPLS network and the WDM optical mesh network is a promising approach to realizing an efficient backbone network. Because of the great volumes of traffic carried, the social cost incurred by a failure will be extremely high, so survivability is very important in the backbone network. In survivable IP/MPLS over WDM backbone networks, cooperation of the optical level fault recovery and the IP/MPLS level fault recovery is essential. This paper analyzes cost characteristics of the optical level fault recovery and the IP/MPLS level fault recovery. A mathematical programming method is proposed to minimize the initial network cost when the IP/MPLS level fault recovery is utilized in the survivable IP/MPLS over WDM networks. Using this method, the initial network cost needed for the IP/MPLS level fault recovery is compared with that for the optical level fault recovery. The initial network cost for the LSP (Label Switched Path) protection scheme is smaller than that for the shared light-path protection scheme and larger than that for the pre-plan type light-path restoration scheme. The LSP protection scheme is suitable for the best-effort type traffic while the shared light-path protection scheme may be suitable for the bandwidth guaranteed type traffic.