In this paper we address the Adjacent Quadratic Assignment Problem (AQAP) which is a variant of the QAP where the cost coefficient matrix has a particular structure. Motivated by strong lower bounds obtained by applying Reformulation Linearization Technique (RLT) to the classical QAP, we propose two special RLT representations for the problem. The first is based on a “flow” formulation whose li...

The article addresses morphological approaches to design of modular systems. The following methods are briefly described: (i) basic version of morphological analysis (MA), (ii) modification of MA as method of closeness to ideal point(s), (iii) reducing of MA to linear programming, (iv) multiple choice problem, (v) quadratic assignment problem, (vi) Pareto-based MA (i.e., revelation of Pareto-ef...

Curriculum design is a highly important activity for the academic institutions. It is discussed in literature as a balancing academic curriculum problem (BACP). The BACP schedules courses to different semesters, while balancing the total workload per period. BACP model involves precedence relations, but the related courses are not necessarily assigned to closest periods. The Relevance Based Cur...

This paper presents an improved as well as a completely new version of a mixed integer linear programming (MILP) formulation for solving the quadratic assignment problem (QAP) to global optimum. Both formulations work especially well on instances where at least one of the matrices is sparse. Modification schemes, to decrease the number of unique elements per row in symmetric instances, are pres...

In this work, we introduce the variance expression for quadratic assignment problem (QAP) costs. We also de;ne classes of QAP instances, described by a common linear relaxation form. The use of the variance in these classes leads to the study of isomorphism and allows for a de;nition of a new di"culty index for QAP instances. This index is then compared to a classical measure found in the liter...

This paper describes what is termed the "generalized assignment problem". It is a generalization of the ordinary assignment problem of linear programming in which multiple assignments of tasks to agents are limited by some resource available to the agents. A branch and bound algorithm is developed that solves the generalized assignment problem by solving a series of binary knapsack problems to ...

The lateral amygdala (LA) acquires differential coding of predictive and non-predictive fear stimuli that is critical for proper fear memory assignment. The neurotransmitter dopamine is an important modulator of LA activity and facilitates fear memory formation, but whether dopamine neurons aid in the establishment of discriminative fear coding by the LA is unknown. NMDA-type glutamate receptor...

We present an explicitly typed lambda calculus “à la Church” based on the union and intersection types discipline; this system is the counterpart of the standard type assignment calculus “à la Curry.” Our typed calculus enjoys Subject Reduction and confluence, and typed terms are strongly normalizing when the universal type is omitted. Moreover both type checking and type reconstruction are dec...