Elective course student sectioning at Danish high schools

Abstract

The Elective Course Student Sectioning (ECSS) problem is an yearly recurrent planning problem at the Danish high schools. The problem is of assigning students to elective course classes given their requests such that as many requests are ful lled and the violation of the soft constraints is minimized. This paper presents an adaptive large neighborhood search heuristic for the ESCC. The algorithm is applied to 80 real-life instances from Danish high schools and compared with solutions found by using the state-of-the-art MIP solver Gurobi. The algorithm has been implemented in the commercial product Lectio, and is thereby available for approximately 200 high schools in Denmark.

Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search

“…The following 25 articles were excluded because the weight adjustment mechanism was not described in detail: [9,10,17,20,29,36,40,41,44,45,47,57,61,65,77,86,90,106,112,116,117,119,122,130,132]. An additional 5 articles [1,22,92,98,133] were excluded because the adaptive layer cannot be removed by setting a parameter to a certain value, and [58] was excluded as a roulette wheel principle is not employed (rather, a heuristic with the highest weight is chosen).…”

Integrated strategic and tactical optimization of animal-waste sourced biopower supply chains

“…As far as heuristic and metaheuristic methods are concerned, no method seems to be widely used by different authors. Adaptive Large Neighbourhood Search (ALNS) has proved to be really efficient for solving optimization problems such as vehicle routing problems, arc scheduling problems, pollution routing, snow-plowing and timetabling problem (see [8], [25], [26], [27], [28], [29], [30] or [31]). However, for solving supply chain network design (SCND) problems, the use of Large Neighbourhood Search (LNS) has been explored by a few studies (see ref.…”