An Efficient Pareto Optimal Resource Allocation Scheme in Cognitive Radio-Based Internet of Things Networks

The high data rates detail that internet-connected devices have been increasing exponentially. Cognitive radio (CR) is an auspicious technology used to address the resource shortage issue in wireless IoT networks. Resource optimization is considered a non-convex and nondeterministic polynomial (NP) complete problem within CR-based Internet of Things (IoT) networks (CR-IoT). Moreover, the combined optimization of conflicting objectives is a challenging issue in CR-IoT networks. In this paper, energy efficiency (EE) and spectral efficiency (SE) are considered as conflicting optimization objectives. This research work proposed a hybrid tabu search-based stimulated algorithm (HTSA) in order to achieve Pareto optimality between EE and SE. In addition, the fuzzy-based decision is employed to achieve better Pareto optimality. The performance of the proposed HTSA approach is analyzed using different resource allocation parameters and validated through simulation results.

Promoting the Solar Industry in Ghana through Effective Public-Private Partnership (PPP): Some Lessons from South Africa and Morocco

Over the past decades, solar energy has gained much attention in Ghana, especially after the 2012–2016 power crisis. The government through Public-Private Partnerships (PPPs) has attempted to increase the shares of solar generation to augment its efforts in reducing the energy deficit of the country, especially in remote and off-grid communities. However, the extent to which PPP has been utilized as a viable tool for solar sector development in Ghana is questionable. This study discusses the current state of PPPs in Ghana’s solar industry and compares how it has been efficiently used as a tool to promote the solar industry in South Africa and Morocco. Fundamental theories such as Altruism, Game, Principal-agent, and Pareto Optimality (PO) were used as analytical tools to examine how PPPs are handled in the selected cases. The study ascertains that the Game and PO are applicable theories that have guided SA and Morocco’s solar infrastructural development. This study discovered that PPP has been efficiently used in SA and Morocco to push its solar industry to be among the best in the world and Ghana can perfectly emulate it. The study further reveals that the Principal-agent analogy and altruistic intent of the Ghanaian government tend to discourage Private sector participation in the solar industry. It further suggests the Pareto Optimality, Game approach, and a win-win transparent attitude towards PPPs. This study recommends a well-developed PPP structure and law for Ghana. It encourages transparency and discourages partisan preferentialism to increase PPPs in Ghana’s solar industry.

Optimality of a Linear Decision Rule in Discrete Time AK Model

Surprisingly, formal proof on the optimality of a linear decision rule in the discrete time AK model with a CRRA utility function has not been established in the growth literature while that in the continuous time counterpart is well-established. This note fills such a gap: I provide a formal proof that consumption being linearly related to investment is a sufficient and necessary condition for Pareto optimality in the discrete time AK model.

Multiobjective Convex Optimization in Real Banach Space

In this paper, we consider convex multiobjective optimization problems with equality and inequality constraints in real Banach space. We establish saddle point necessary and sufficient Pareto optimality conditions for considered problems under some constraint qualifications. These results are motivated by the symmetric results obtained in the recent article by Cobos Sánchez et al. in 2021 on Pareto optimality for multiobjective optimization problems of continuous linear operators. The discussions in this paper are also related to second order symmetric duality for nonlinear multiobjective mixed integer programs for arbitrary cones due to Mishra and Wang in 2005. Further, we establish Karush–Kuhn–Tucker optimality conditions using saddle point optimality conditions for the differentiable cases and present some examples to illustrate our results. The study in this article can also be seen and extended as symmetric results of necessary and sufficient optimality conditions for vector equilibrium problems on Hadamard manifolds by Ruiz-Garzón et al. in 2019.

Weighted Envy-freeness in Indivisible Item Allocation

We introduce and analyze new envy-based fairness concepts for agents with weights that quantify their entitlements in the allocation of indivisible items. We propose two variants of weighted envy-freeness up to one item (WEF1): strong , where envy can be eliminated by removing an item from the envied agent’s bundle, and weak , where envy can be eliminated either by removing an item (as in the strong version) or by replicating an item from the envied agent’s bundle in the envying agent’s bundle. We show that for additive valuations, an allocation that is both Pareto optimal and strongly WEF1 always exists and can be computed in pseudo-polynomial time; moreover, an allocation that maximizes the weighted Nash social welfare may not be strongly WEF1, but it always satisfies the weak version of the property. Moreover, we establish that a generalization of the round-robin picking sequence algorithm produces in polynomial time a strongly WEF1 allocation for an arbitrary number of agents; for two agents, we can efficiently achieve both strong WEF1 and Pareto optimality by adapting the adjusted winner procedure. Our work highlights several aspects in which weighted fair division is richer and more challenging than its unweighted counterpart.