Determining adjacent vertices on assignment polytopes

To rank the solutions to the assignment problem using an extreme point method, it is necessary to be able to find all extreme points which are adjacent to a given extreme solution. Recent work has shown a procedure for determining adjacent vertices on transportation polytopes using a modification of the Chernikova Algorithm. We present here a procedure for assignment polytopes which is a simplification of the more general procedure for transportation polytopes and which also allows for implicit enumeration of adjacent vertices.     

Local perceptions of the EU’s role in peacebuilding: The case of security sector reform in Palestine

ABSTRACT

Perception research can make a valuable contribution to the study of the local dimension in EU peacebuilding. The conceptual framework developed in this article distinguishes between perceptions of the “legitimacy,” “effectiveness,” and “credibility” of EU peacebuilding practices, which are crucial factors for successful peacebuilding. Relying on the case of the EU’s support for security sector reform (SSR) in Palestine, this article shows that local stakeholders—which participate in various EU-sponsored training and capacity-building programs—display considerable support for liberal peacebuilding norms. Yet, perceived discrepancies between the EU’s peacebuilding rhetoric and its SSR activities have severely undermined the potential of the EU’s liberal peacebuilding model in the eyes of Palestinian stakeholders. Critical local perceptions are frequently articulated with reference to the EU’s own liberal peacebuilding discourse, pointing to a lack of inclusiveness of the SSR process and deficits in terms of democratic governance and the rule of law.     

Aggregating courier deliveries

We consider the problem of efficiently scheduling deliveries by an uncapacitated courier from a central location under online arrivals. We consider both adversary‐controlled and Poisson arrival processes. In the adversarial setting we provide a randomized (3βΔ/2δ ? 1) ‐competitive algorithm, where β is the approximation ratio of the traveling salesman problem, δ is the minimum distance between the central location and any customer, and Δ is the length of the optimal traveling salesman tour overall customer locations and the central location. We provide instances showing that this analysis is tight. We also prove a 1 + 0.271Δ/δ lower‐bound on the competitive ratio of any algorithm in this setting. In the Poisson setting, we relax our assumption of deterministic travel times by assuming that travel times are distributed with a mean equal to the excursion length. We prove that optimal policies in this setting follow a threshold structure and describe this structure. For the half‐line metric space we bound the performance of the randomized algorithm in the Poisson setting, and show through numerical experiments that the performance of the algorithm is often much better than this bound.     

A branch-and-bound algorithm for solving fixed charge problems

Numerous procedures have been suggested for solving fixed charge problems. Among these are branch-and-bound methods, cutting plane methods, and vertex ranking methods. In all of these previous approaches, the procedure depends heavily on the continuous costs to terminate the search for the optimal solution. In this paper, we present a new branch-and-bound algorithm that calculates bounds separately on the sum of fixed costs and on the continuous objective value. Computational experience is shown for various standard test problems as well as for randomly generated problems. These test results are compared to previous procedures as well as to a mixed integer code. These comparisons appear promising.     

The pure fixed charge transportation problem

The pure fixed charge transportation problem (PFCTP) is a variation of the fixed charge transportation problem (FCTP) in which there are only fixed costs to be incurred when a route is opened. We present in this paper a direct search procedure using the LIFO decision rule for branching. This procedure is enhanced by the use of 0–1 knapsack problems which determine bounds on partial solutions. Computational results are presented and discussed.